Parte 2: Reconocimiento de objetos¶
Cargamos las imágenes
import os
import numpy as np
from skimage.io import imread
from skimage.color import gray2rgb
from skimage.transform import resize
from skimage import exposure
from scipy.ndimage import rotate, shift
# Rutas de imágenes y máscaras
ruta_imagenes = r"C:\Users\norae\piva_enrique\Materiales1\objects\objects\images"
ruta_mascaras = r"C:\Users\norae\piva_enrique\Materiales1\objects\objects\masks"
# Diccionario de clases simplificado
clases = {
'elephant': 0,
'rhino': 1,
'emu': 2, # se etiquetará como "otros"
'flamingo': 2 # también como "otros"
}
# Tamaño objetivo para redimensionar las imágenes
tamaño_objetivo = (200, 300)
# Función para cargar imágenes con su clase
def cargar_imagenes_objeto(ruta_base, clases, tamaño_objetivo):
imagenes = []
etiquetas = []
for nombre_clase in os.listdir(ruta_base):
if nombre_clase not in clases:
continue
etiqueta = clases[nombre_clase]
ruta_clase = os.path.join(ruta_base, nombre_clase)
nombres_archivos = sorted(os.listdir(ruta_clase))
for nombre_archivo in nombres_archivos:
ruta_imagen = os.path.join(ruta_clase, nombre_archivo)
imagen = imread(ruta_imagen) / 255.0
if imagen.ndim == 2:
imagen = gray2rgb(imagen)
imagen_redim = resize(imagen, tamaño_objetivo, anti_aliasing=True)
imagenes.append(imagen_redim)
etiquetas.append(etiqueta)
return np.array(imagenes, dtype=np.float32), np.array(etiquetas)
# Función para cargar las máscaras
def cargar_mascaras(ruta_mascaras, clases, tamaño_objetivo):
mascaras = []
for nombre_clase in os.listdir(ruta_mascaras):
if nombre_clase not in clases:
continue
ruta_clase = os.path.join(ruta_mascaras, nombre_clase)
nombres_archivos = sorted(os.listdir(ruta_clase))
for nombre_archivo in nombres_archivos:
ruta_mascara = os.path.join(ruta_clase, nombre_archivo)
imagen = imread(ruta_mascara) / 255.0
imagen_redim = resize(imagen, tamaño_objetivo)
mascara_binaria = (imagen_redim > 0.5).astype(np.uint8)
mascaras.append(mascara_binaria)
return np.array(mascaras)
# Función para aumentar el dataset
def aumentar_dataset_manual(imagenes, mascaras, etiquetas, n_augmentaciones=2):
imagenes_aug = []
mascaras_aug = []
etiquetas_aug = []
for img, mask, label in zip(imagenes, mascaras, etiquetas):
imagenes_aug.append(img)
mascaras_aug.append(mask)
etiquetas_aug.append(label)
for _ in range(n_augmentaciones):
img_aug = img.copy()
mask_aug = mask.copy()
# Flip horizontal
if np.random.rand() > 0.5:
img_aug = np.fliplr(img_aug)
mask_aug = np.fliplr(mask_aug)
# Flip vertical
if np.random.rand() > 0.5:
img_aug = np.flipud(img_aug)
mask_aug = np.flipud(mask_aug)
# Rotación aleatoria
angle = np.random.uniform(-20, 20)
img_aug = rotate(img_aug, angle, reshape=False, mode='reflect')
mask_aug = rotate(mask_aug, angle, reshape=False, mode='nearest')
# Desplazamiento aleatorio
shift_x = np.random.uniform(-10, 10)
shift_y = np.random.uniform(-10, 10)
img_aug = shift(img_aug, shift=(shift_x, shift_y, 0), mode='reflect')
mask_aug = shift(mask_aug, shift=(shift_x, shift_y), mode='nearest')
# Ajuste de brillo/contraste
if np.random.rand() > 0.5:
gamma = np.random.uniform(0.8, 1.2)
img_aug = exposure.rescale_intensity(img_aug, in_range='image', out_range=(0, 1))
img_aug = exposure.adjust_gamma(img_aug, gamma=gamma)
img_aug = np.clip(img_aug, 0, 1)
imagenes_aug.append(img_aug)
mascaras_aug.append((mask_aug > 0.5).astype(np.uint8))
etiquetas_aug.append(label)
return np.array(imagenes_aug), np.array(mascaras_aug), np.array(etiquetas_aug)
# Cargar datos filtrados
imagenes, etiquetas = cargar_imagenes_objeto(ruta_imagenes, clases, tamaño_objetivo)
mascaras = cargar_mascaras(ruta_mascaras, clases, tamaño_objetivo)
# Aumentar el dataset
imagenes_aug, mascaras_aug, etiquetas_aug = aumentar_dataset_manual(imagenes, mascaras, etiquetas, n_augmentaciones=2)
# Verificación
print(f"Número total de imágenes aumentadas: {imagenes_aug.shape[0]}")
indice = 43
print(f"Imagen {indice} - shape: {imagenes[indice].shape}, etiqueta: {etiquetas[indice]}")
print(f"Mascara {indice} - shape: {mascaras[indice].shape}, valores únicos: {np.unique(mascaras[indice])}")
Número total de imágenes aumentadas: 729 Imagen 43 - shape: (200, 300, 3), etiqueta: 0 Mascara 43 - shape: (200, 300), valores únicos: [0 1]
Vemos las imágenes
import matplotlib.pyplot as plt
def mostrar_galeria(imagenes, titulos=None, filas=3, columnas=5, cmap=None, suptitulo=None):
total = filas * columnas
fig, axes = plt.subplots(filas, columnas, figsize=(16, 12))
for i, ax in enumerate(axes.flat):
if i < len(imagenes):
imagen = imagenes[i]
ax.imshow(imagen, cmap=cmap if imagen.ndim == 2 else None)
if titulos:
ax.set_title(str(titulos[i]))
ax.axis('off')
else:
ax.axis('off')
if suptitulo:
plt.subplots_adjust(top=0.9)
fig.suptitle(suptitulo, fontsize=18)
plt.tight_layout()
plt.show()
# Títulos opcionales
titulos_animales = [f'Clase: {etiquetas[i]}' for i in range(len(imagenes))]
titulos_mascaras = [f'Máscara {i+1}' for i in range(len(mascaras))]
# Visualizar primeras 15 imágenes
mostrar_galeria(imagenes[:15], titulos_animales[:15], filas=3, columnas=5, suptitulo='Imágenes originales')
# Visualizar primeras 15 máscaras
mostrar_galeria(mascaras[:15], titulos_mascaras[:15], filas=3, columnas=5, cmap='gray', suptitulo='Máscaras binarizadas')
Extraemos las características del espacio RGB
def obtener_medias_rgb(imagenes, mascaras):
caracteristicas_figura = []
caracteristicas_fondo = []
for idx in range(len(imagenes)):
img = imagenes[idx]
mask = mascaras[idx]
# Separar canales RGB
r, g, b = img[:, :, 0], img[:, :, 1], img[:, :, 2]
# Índices booleanos para figura (1) y fondo (0)
indices_figura = mask == 1
indices_fondo = mask == 0
# Evitar errores si alguna zona no existe en la máscara
if not np.any(indices_figura):
media_figura = [0.0, 0.0, 0.0]
else:
media_figura = [
np.mean(r[indices_figura]),
np.mean(g[indices_figura]),
np.mean(b[indices_figura])
]
if not np.any(indices_fondo):
media_fondo = [0.0, 0.0, 0.0]
else:
media_fondo = [
np.mean(r[indices_fondo]),
np.mean(g[indices_fondo]),
np.mean(b[indices_fondo])
]
caracteristicas_figura.append(media_figura)
caracteristicas_fondo.append(media_fondo)
return (
np.array(caracteristicas_figura, dtype=np.float32),
np.array(caracteristicas_fondo, dtype=np.float32)
)
Extraemos el contorno de los animales
from skimage.measure import label, regionprops
import numpy as np
def extraer_ratio_area_contorno(mascaras_binarias):
ratios = []
for mascara in mascaras_binarias:
# Etiquetar regiones conectadas
etiqueta = label(mascara)
# Extraer propiedades
regiones = regionprops(etiqueta)
if len(regiones) > 0:
# Tomamos la región de mayor área
region_principal = max(regiones, key=lambda r: r.area)
area_real = region_principal.area
minr, minc, maxr, maxc = region_principal.bbox
alto = maxr - minr
ancho = maxc - minc
area_rect = alto * ancho
proporcion = area_real / area_rect if area_rect > 0 else 0.0
ratios.append(proporcion)
else:
ratios.append(0.0)
return np.array(ratios, dtype=np.float32).reshape(-1, 1)
Extraemos texturas mediante orientación de gradiente
from scipy.ndimage import gaussian_filter
from skimage import color
import numpy as np
def generar_mapa_direcciones(angulo_grad, num_direcciones):
# Calcula el ancho (en grados) de cada sector angular
paso = 360 / num_direcciones
# Define los centros de cada sector en el rango [-180, 180]
sectores = np.linspace(-180, 180, num_direcciones)
# Inicializa un mapa 3D (alto x ancho x num_direcciones) con ceros
mapa_direcciones = np.zeros((*angulo_grad.shape, num_direcciones), dtype=int)
# Para cada sector direccional, marca los píxeles que caen dentro del ángulo
for idx, centro in enumerate(sectores):
# Crea una máscara binaria donde el ángulo está dentro del sector
dentro_sector = np.abs(angulo_grad - centro) < paso / 2
# Almacena esa máscara en la capa correspondiente del mapa
mapa_direcciones[:, :, idx] = dentro_sector.astype(int)
# Devuelve el mapa direccional codificado como capas binarias
return mapa_direcciones
def extraer_caracteristicas_textura(imagenes, mascaras):
textura_total = [] # Lista para almacenar histogramas de cada imagen
suavizado_sigma = 1 # Valor sigma para el filtro gaussiano
# Itera sobre todas las imágenes y sus respectivas máscaras
for img, mask in zip(imagenes, mascaras):
# Convierte la imagen a escala de grises para análisis de gradiente
img_gray = color.rgb2gray(img)
# Aplica un suavizado Gaussiano para reducir el ruido antes del gradiente
suavizada = gaussian_filter(img_gray, sigma=suavizado_sigma)
# Calcula el gradiente en x (horizontal) y en y (vertical)
grad_x = np.gradient(suavizada, axis=1)
grad_y = np.gradient(suavizada, axis=0)
# Calcula el ángulo de orientación del gradiente en grados
orientacion = np.arctan2(grad_y, grad_x) * (180 / np.pi)
# Convierte los ángulos en un mapa de direcciones discretas
mapa = generar_mapa_direcciones(orientacion, 8)
# Aplica la máscara binaria a cada canal direccional (solo figura)
direcciones_validas = mapa * mask[:, :, np.newaxis]
# Suma los valores válidos por canal direccional → histograma 1D de 8 valores
histograma = np.sum(direcciones_validas, axis=(0, 1))
# Normaliza el histograma para que represente proporciones
histograma_norm = histograma / np.sum(histograma)
# Almacena el histograma normalizado como características de textura
textura_total.append(histograma_norm)
# Devuelve una matriz (n_imágenes x 8) con los histogramas de textura
return np.array(textura_total)
import numpy as np
# Extracción de características usando las imágenes aumentadas
caracteristicas_figura, caracteristicas_fondo = obtener_medias_rgb(imagenes_aug, mascaras_aug)
caracteristicas_contorno1 = extraer_ratio_area_contorno(mascaras_aug)
caracteristicas_textura = extraer_caracteristicas_textura(imagenes_aug, mascaras_aug)
# Construcción del conjunto de características y etiquetas
X = np.hstack([
caracteristicas_figura,
caracteristicas_fondo,
caracteristicas_contorno1,
caracteristicas_textura
])
y = etiquetas_aug
imgs = imagenes_aug
masks = mascaras_aug
# Verificación de dimensiones
print(" Dimensiones de las características:")
print(f" RGB figura: {caracteristicas_figura.shape}")
print(f" RGB fondo: {caracteristicas_fondo.shape}")
print(f" Contorno (área): {caracteristicas_contorno1.shape}")
print(f" Texturas direccionales: {caracteristicas_textura.shape}")
print(f" Conjunto unificado: {X.shape}")
Dimensiones de las características: RGB figura: (729, 3) RGB fondo: (729, 3) Contorno (área): (729, 1) Texturas direccionales: (729, 8) Conjunto unificado: (729, 15)
import matplotlib.pyplot as plt
from skimage import color
from skimage.measure import label, regionprops, moments, moments_hu
from scipy.ndimage import gaussian_filter
import numpy as np
def visualizar_caracteristicas(imagen, mascara, mostrar_texto=True):
fig, axs = plt.subplots(2, 3, figsize=(15, 10))
axs = axs.ravel()
# Imagen original
axs[0].imshow(imagen)
axs[0].set_title("Imagen original")
axs[0].axis('off')
# Máscara binaria (figura)
axs[1].imshow(mascara, cmap='gray')
axs[1].set_title("Máscara (figura)")
axs[1].axis('off')
# Fondo enmascarado
fondo = imagen.copy()
fondo[mascara == 1] = 0
axs[2].imshow(fondo)
axs[2].set_title("Fondo (imagen sin figura)")
axs[2].axis('off')
# Ángulo del gradiente
imagen_gris = color.rgb2gray(imagen)
suavizada = gaussian_filter(imagen_gris, sigma=1)
dx = np.gradient(suavizada, axis=1)
dy = np.gradient(suavizada, axis=0)
angulo = np.arctan2(dy, dx) * (180 / np.pi)
axs[3].imshow(angulo, cmap='twilight', vmin=-180, vmax=180)
axs[3].set_title("Ángulo del gradiente")
axs[3].axis('off')
# Histograma de direcciones
direcciones = generar_mapa_direcciones(angulo, 8)
direcciones_mascaradas = direcciones * mascara[:, :, np.newaxis]
frecuencias = np.sum(direcciones_mascaradas, axis=(0, 1))
axs[4].bar(range(8), frecuencias)
axs[4].set_title("Histograma de direcciones")
axs[4].set_xlabel("Sector")
axs[4].set_ylabel("Frecuencia")
# Datos numéricos
if mostrar_texto:
# Medias RGB figura
rgb_figura = imagen[mascara == 1]
media_rgb = np.mean(rgb_figura, axis=0)
# Momentos de Hu con skimage
etiqueta = label(mascara)
regiones = regionprops(etiqueta)
texto = "Medias RGB figura:\n" + \
f"R: {media_rgb[0]:.2f} G: {media_rgb[1]:.2f} B: {media_rgb[2]:.2f}\n\n"
axs[5].axis('off')
axs[5].text(0.01, 0.95, texto, fontsize=10, verticalalignment='top')
else:
axs[5].axis('off')
plt.tight_layout()
plt.show()
# Ejemplo de uso
visualizar_caracteristicas(imagenes[0], mascaras[0])
Definimos el modelo y entrenamos con todas las característicaas extraídas
Dividimos los datos en entrenamiento y test
from sklearn.model_selection import train_test_split
# División del dataset en entrenamiento y prueba
X_train, X_test, y_train, y_test, imgs_train, imgs_test, masks_train, masks_test = train_test_split(
X, y, imgs, masks, test_size=0.2, random_state=42, stratify=y
)
# Información sobre la división
print("\nDivisión del dataset:")
print("────────────────────────────")
print("Conjunto de entrenamiento:")
print(f" X_train: {X_train.shape}")
print(f" y_train: {y_train.shape}")
print(f" imgs_train: {imgs_train.shape}")
print(f" masks_train: {masks_train.shape}")
print("\nConjunto de prueba:")
print(f" X_test: {X_test.shape}")
print(f" y_test: {y_test.shape}")
print(f" imgs_test: {imgs_test.shape}")
print(f" masks_test: {masks_test.shape}")
División del dataset: ──────────────────────────── Conjunto de entrenamiento: X_train: (583, 15) y_train: (583,) imgs_train: (583, 200, 300, 3) masks_train: (583, 200, 300) Conjunto de prueba: X_test: (146, 15) y_test: (146,) imgs_test: (146, 200, 300, 3) masks_test: (146, 200, 300)
Vamos a probar distintas combinaciones de hiperparámetros para ver cuáles son mejores para nuestro entrenamiento
Se comparan mediante el f1-score ya que busca equilibrio entre precision y recall, solo será alto si ambos son altos.
from sklearn.preprocessing import StandardScaler
from tensorflow.keras.utils import to_categorical
# Reemplazar valores no finitos por ceros
X_train = np.nan_to_num(X_train, nan=0.0, posinf=0.0, neginf=0.0)
X_test = np.nan_to_num(X_test, nan=0.0, posinf=0.0, neginf=0.0)
# Escalado estándar de los datos de entrada
normalizer = StandardScaler()
X_train_scaled = normalizer.fit_transform(X_train)
X_test_scaled = normalizer.transform(X_test)
# Conversión explícita de etiquetas a enteros y luego a one-hot encoding (float32)
y_train = y_train.astype("int32")
y_test = y_test.astype("int32")
Y_train_onehot = to_categorical(y_train, num_classes=3).astype("float32")
Y_test_onehot = to_categorical(y_test, num_classes=3).astype("float32")
# Definición de los hiperparámetros a probar
lr_options = [0.001, 0.01, 0.1]
dropout_values = [0.4, 0.6, 0.8]
batch_options = [4, 8, 16]
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
from keras.models import Sequential
from keras.layers import Dense, Dropout, Input, BatchNormalization
from keras.optimizers import Adam
# Número de clases de salida (según el one-hot encoding)
n_classes = Y_train_onehot.shape[1]
# Lista para almacenar los resultados de evaluación del modelo
eval_metrics = []
# Bucle de búsqueda de hiperparámetros
for lr in lr_options:
for drop in dropout_values:
for batch in batch_options:
# Definición de la arquitectura de la red neuronal
network = Sequential([
Input(shape=(X_train_scaled.shape[1],)),
Dense(256, activation='relu'),
BatchNormalization(),
Dropout(drop),
Dense(128, activation='tanh'),
Dropout(drop),
Dense(64, activation='relu'),
Dropout(drop),
Dense(32, activation='relu'),
Dropout(drop),
Dense(16, activation='relu'),
Dense(n_classes, activation='softmax') # Capa de salida con softmax para clasificación multiclase
])
# Compilación del modelo
network.compile(
optimizer=Adam(learning_rate=lr),
loss='categorical_crossentropy',
metrics=['accuracy', 'Precision', 'Recall', 'AUC']
)
# Entrenamiento del modelo
network.fit(X_train_scaled, Y_train_onehot, epochs=50, batch_size=batch, verbose=1)
# Predicción sobre el conjunto de test
preds = network.predict(X_test_scaled)
pred_labels = np.argmax(preds, axis=1)
true_labels = np.argmax(Y_test_onehot, axis=1)
# Cálculo de las métricas de evaluación
acc = accuracy_score(true_labels, pred_labels)
prec = precision_score(true_labels, pred_labels, average='macro', zero_division=0.0)
rec = recall_score(true_labels, pred_labels, average='macro', zero_division=0.0)
f1 = f1_score(true_labels, pred_labels, average='macro', zero_division=0.0)
# Almacenamiento de las métricas junto con los hiperparámetros usados
eval_metrics.append({
'learning_rate': lr,
'dropout_rate': drop,
'batch_size': batch,
'accuracy': acc,
'precision': prec,
'recall': rec,
'f1': f1
})
# Selección de la mejor configuración según el F1-score
optimal_config = max(eval_metrics, key=lambda res: res['f1'])
print("Mejor combinación de hiperparámetros:")
print(optimal_config)
Epoch 1/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 9s 6ms/step - AUC: 0.5121 - Precision: 0.3715 - Recall: 0.1919 - accuracy: 0.3538 - loss: 1.2963 Epoch 2/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6900 - Precision: 0.6262 - Recall: 0.3423 - accuracy: 0.4889 - loss: 1.0122 Epoch 3/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7756 - Precision: 0.7009 - Recall: 0.4040 - accuracy: 0.5893 - loss: 0.9036 Epoch 4/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7935 - Precision: 0.7043 - Recall: 0.4510 - accuracy: 0.6052 - loss: 0.8381 Epoch 5/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7893 - Precision: 0.6839 - Recall: 0.4344 - accuracy: 0.5984 - loss: 0.8475 Epoch 6/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8055 - Precision: 0.7031 - Recall: 0.4407 - accuracy: 0.6147 - loss: 0.8395 Epoch 7/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8088 - Precision: 0.6982 - Recall: 0.4565 - accuracy: 0.5962 - loss: 0.7999 Epoch 8/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8393 - Precision: 0.7609 - Recall: 0.5030 - accuracy: 0.6233 - loss: 0.7480 Epoch 9/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8131 - Precision: 0.6982 - Recall: 0.4632 - accuracy: 0.6176 - loss: 0.8385 Epoch 10/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8260 - Precision: 0.7712 - Recall: 0.4851 - accuracy: 0.6268 - loss: 0.7765 Epoch 11/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8273 - Precision: 0.7209 - Recall: 0.4838 - accuracy: 0.6026 - loss: 0.7666 Epoch 12/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8458 - Precision: 0.7447 - Recall: 0.5010 - accuracy: 0.6499 - loss: 0.7495 Epoch 13/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8338 - Precision: 0.7884 - Recall: 0.4881 - accuracy: 0.6368 - loss: 0.7776 Epoch 14/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8166 - Precision: 0.6907 - Recall: 0.4576 - accuracy: 0.6020 - loss: 0.8034 Epoch 15/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8266 - Precision: 0.7666 - Recall: 0.4693 - accuracy: 0.6124 - loss: 0.7656 Epoch 16/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8427 - Precision: 0.7571 - Recall: 0.4793 - accuracy: 0.6419 - loss: 0.7315 Epoch 17/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8394 - Precision: 0.7568 - Recall: 0.4893 - accuracy: 0.6109 - loss: 0.7260 Epoch 18/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8626 - Precision: 0.7782 - Recall: 0.5038 - accuracy: 0.6639 - loss: 0.6845 Epoch 19/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8510 - Precision: 0.7395 - Recall: 0.5045 - accuracy: 0.6428 - loss: 0.7286 Epoch 20/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8567 - Precision: 0.7797 - Recall: 0.4779 - accuracy: 0.6145 - loss: 0.6823 Epoch 21/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8510 - Precision: 0.7536 - Recall: 0.4871 - accuracy: 0.6120 - loss: 0.7216 Epoch 22/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8400 - Precision: 0.7252 - Recall: 0.4631 - accuracy: 0.6177 - loss: 0.7426 Epoch 23/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8530 - Precision: 0.7528 - Recall: 0.4674 - accuracy: 0.6604 - loss: 0.7004 Epoch 24/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8552 - Precision: 0.8036 - Recall: 0.4888 - accuracy: 0.6433 - loss: 0.7016 Epoch 25/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8509 - Precision: 0.7448 - Recall: 0.5486 - accuracy: 0.6385 - loss: 0.7524 Epoch 26/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8641 - Precision: 0.7498 - Recall: 0.4894 - accuracy: 0.6669 - loss: 0.6942 Epoch 27/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8396 - Precision: 0.7518 - Recall: 0.4992 - accuracy: 0.6352 - loss: 0.7509 Epoch 28/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8595 - Precision: 0.7055 - Recall: 0.5045 - accuracy: 0.6429 - loss: 0.7259 Epoch 29/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8615 - Precision: 0.7577 - Recall: 0.5221 - accuracy: 0.6608 - loss: 0.7114 Epoch 30/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8505 - Precision: 0.7689 - Recall: 0.5026 - accuracy: 0.6611 - loss: 0.7240 Epoch 31/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8810 - Precision: 0.7836 - Recall: 0.5742 - accuracy: 0.6810 - loss: 0.6373 Epoch 32/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8862 - Precision: 0.7932 - Recall: 0.5529 - accuracy: 0.7070 - loss: 0.6444 Epoch 33/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8719 - Precision: 0.7953 - Recall: 0.5444 - accuracy: 0.6743 - loss: 0.6593 Epoch 34/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8898 - Precision: 0.8055 - Recall: 0.5991 - accuracy: 0.7061 - loss: 0.6380 Epoch 35/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8859 - Precision: 0.7794 - Recall: 0.5878 - accuracy: 0.7085 - loss: 0.6332 Epoch 36/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8642 - Precision: 0.7251 - Recall: 0.5004 - accuracy: 0.6232 - loss: 0.6611 Epoch 37/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8849 - Precision: 0.7453 - Recall: 0.5529 - accuracy: 0.6861 - loss: 0.6163 Epoch 38/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8846 - Precision: 0.8032 - Recall: 0.5642 - accuracy: 0.6576 - loss: 0.6192 Epoch 39/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8580 - Precision: 0.7444 - Recall: 0.5380 - accuracy: 0.6589 - loss: 0.7297 Epoch 40/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8552 - Precision: 0.7181 - Recall: 0.4969 - accuracy: 0.6496 - loss: 0.7259 Epoch 41/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8777 - Precision: 0.7453 - Recall: 0.5581 - accuracy: 0.6840 - loss: 0.6449 Epoch 42/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8818 - Precision: 0.7605 - Recall: 0.5871 - accuracy: 0.7014 - loss: 0.6323 Epoch 43/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8956 - Precision: 0.7865 - Recall: 0.6003 - accuracy: 0.7135 - loss: 0.6022 Epoch 44/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.9087 - Precision: 0.7993 - Recall: 0.6172 - accuracy: 0.7459 - loss: 0.5780 Epoch 45/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8661 - Precision: 0.7559 - Recall: 0.5881 - accuracy: 0.6926 - loss: 0.6832 Epoch 46/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8809 - Precision: 0.7669 - Recall: 0.5760 - accuracy: 0.7148 - loss: 0.6467 Epoch 47/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8462 - Precision: 0.7347 - Recall: 0.5227 - accuracy: 0.6275 - loss: 0.7322 Epoch 48/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8861 - Precision: 0.7896 - Recall: 0.5407 - accuracy: 0.6884 - loss: 0.6267 Epoch 49/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8811 - Precision: 0.7848 - Recall: 0.5299 - accuracy: 0.6875 - loss: 0.6527 Epoch 50/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8632 - Precision: 0.7376 - Recall: 0.5449 - accuracy: 0.6401 - loss: 0.6841 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 35ms/step Epoch 1/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 4s 4ms/step - AUC: 0.4733 - Precision: 0.3092 - Recall: 0.1456 - accuracy: 0.3102 - loss: 1.3131 Epoch 2/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7447 - Precision: 0.6725 - Recall: 0.3489 - accuracy: 0.5820 - loss: 0.9345 Epoch 3/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7655 - Precision: 0.7384 - Recall: 0.4145 - accuracy: 0.5632 - loss: 0.8679 Epoch 4/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7782 - Precision: 0.6927 - Recall: 0.3773 - accuracy: 0.5736 - loss: 0.8620 Epoch 5/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8297 - Precision: 0.7269 - Recall: 0.4611 - accuracy: 0.6156 - loss: 0.7694 Epoch 6/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8543 - Precision: 0.7576 - Recall: 0.4954 - accuracy: 0.6593 - loss: 0.7249 Epoch 7/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8716 - Precision: 0.8009 - Recall: 0.5399 - accuracy: 0.6782 - loss: 0.6725 Epoch 8/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8384 - Precision: 0.7318 - Recall: 0.4350 - accuracy: 0.6299 - loss: 0.7565 Epoch 9/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8628 - Precision: 0.8205 - Recall: 0.5452 - accuracy: 0.6711 - loss: 0.7329 Epoch 10/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8710 - Precision: 0.7900 - Recall: 0.4978 - accuracy: 0.6279 - loss: 0.6594 Epoch 11/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.8779 - Precision: 0.7771 - Recall: 0.5511 - accuracy: 0.6986 - loss: 0.6712 Epoch 12/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8773 - Precision: 0.8026 - Recall: 0.5284 - accuracy: 0.7076 - loss: 0.6564 Epoch 13/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8633 - Precision: 0.7502 - Recall: 0.4951 - accuracy: 0.6648 - loss: 0.6729 Epoch 14/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8762 - Precision: 0.7894 - Recall: 0.5340 - accuracy: 0.6824 - loss: 0.6756 Epoch 15/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8751 - Precision: 0.7396 - Recall: 0.5382 - accuracy: 0.6596 - loss: 0.6306 Epoch 16/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8818 - Precision: 0.7689 - Recall: 0.5613 - accuracy: 0.7003 - loss: 0.6343 Epoch 17/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8891 - Precision: 0.7615 - Recall: 0.5764 - accuracy: 0.6860 - loss: 0.5933 Epoch 18/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8723 - Precision: 0.7257 - Recall: 0.5410 - accuracy: 0.6424 - loss: 0.6255 Epoch 19/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8890 - Precision: 0.8146 - Recall: 0.5804 - accuracy: 0.6890 - loss: 0.6301 Epoch 20/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8893 - Precision: 0.7792 - Recall: 0.5847 - accuracy: 0.7076 - loss: 0.6244 Epoch 21/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8937 - Precision: 0.7666 - Recall: 0.5721 - accuracy: 0.6863 - loss: 0.5848 Epoch 22/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8984 - Precision: 0.7756 - Recall: 0.5984 - accuracy: 0.6947 - loss: 0.5847 Epoch 23/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8868 - Precision: 0.7676 - Recall: 0.5615 - accuracy: 0.6857 - loss: 0.6201 Epoch 24/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8718 - Precision: 0.7273 - Recall: 0.5453 - accuracy: 0.6443 - loss: 0.6382 Epoch 25/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8791 - Precision: 0.7786 - Recall: 0.5398 - accuracy: 0.6653 - loss: 0.6435 Epoch 26/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8961 - Precision: 0.7720 - Recall: 0.5864 - accuracy: 0.6820 - loss: 0.5786 Epoch 27/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8882 - Precision: 0.7941 - Recall: 0.5795 - accuracy: 0.7069 - loss: 0.6312 Epoch 28/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8964 - Precision: 0.7936 - Recall: 0.5930 - accuracy: 0.6963 - loss: 0.5750 Epoch 29/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9208 - Precision: 0.8017 - Recall: 0.6312 - accuracy: 0.7427 - loss: 0.5052 Epoch 30/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9041 - Precision: 0.7718 - Recall: 0.6010 - accuracy: 0.7143 - loss: 0.5600 Epoch 31/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9026 - Precision: 0.7760 - Recall: 0.6162 - accuracy: 0.6960 - loss: 0.5602 Epoch 32/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9147 - Precision: 0.8089 - Recall: 0.5939 - accuracy: 0.7353 - loss: 0.5333 Epoch 33/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9007 - Precision: 0.7637 - Recall: 0.6140 - accuracy: 0.6990 - loss: 0.5581 Epoch 34/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9186 - Precision: 0.8070 - Recall: 0.6693 - accuracy: 0.7441 - loss: 0.5277 Epoch 35/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8928 - Precision: 0.7278 - Recall: 0.5837 - accuracy: 0.6802 - loss: 0.5990 Epoch 36/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8849 - Precision: 0.7537 - Recall: 0.5883 - accuracy: 0.6737 - loss: 0.6249 Epoch 37/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8963 - Precision: 0.7438 - Recall: 0.5505 - accuracy: 0.6850 - loss: 0.5682 Epoch 38/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9056 - Precision: 0.7683 - Recall: 0.5853 - accuracy: 0.7125 - loss: 0.5546 Epoch 39/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9285 - Precision: 0.8380 - Recall: 0.6754 - accuracy: 0.7689 - loss: 0.4904 Epoch 40/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8843 - Precision: 0.7022 - Recall: 0.5707 - accuracy: 0.6493 - loss: 0.6114 Epoch 41/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9085 - Precision: 0.7538 - Recall: 0.6165 - accuracy: 0.7230 - loss: 0.5299 Epoch 42/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9325 - Precision: 0.8397 - Recall: 0.6908 - accuracy: 0.7979 - loss: 0.4901 Epoch 43/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8893 - Precision: 0.7400 - Recall: 0.5992 - accuracy: 0.6915 - loss: 0.6150 Epoch 44/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9216 - Precision: 0.7764 - Recall: 0.6862 - accuracy: 0.7517 - loss: 0.5181 Epoch 45/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9180 - Precision: 0.7826 - Recall: 0.6699 - accuracy: 0.7494 - loss: 0.5179 Epoch 46/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9140 - Precision: 0.7878 - Recall: 0.6412 - accuracy: 0.7231 - loss: 0.5336 Epoch 47/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9130 - Precision: 0.7673 - Recall: 0.6621 - accuracy: 0.7158 - loss: 0.5353 Epoch 48/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9177 - Precision: 0.7833 - Recall: 0.6269 - accuracy: 0.7308 - loss: 0.5305 Epoch 49/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9217 - Precision: 0.8000 - Recall: 0.6821 - accuracy: 0.7526 - loss: 0.5200 Epoch 50/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9240 - Precision: 0.7712 - Recall: 0.6685 - accuracy: 0.7334 - loss: 0.4835 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 60ms/step Epoch 1/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 4s 5ms/step - AUC: 0.5042 - Precision: 0.3257 - Recall: 0.2110 - accuracy: 0.3269 - loss: 1.3456 Epoch 2/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7058 - Precision: 0.6238 - Recall: 0.3769 - accuracy: 0.5109 - loss: 0.9954 Epoch 3/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7527 - Precision: 0.7180 - Recall: 0.4008 - accuracy: 0.5495 - loss: 0.9285 Epoch 4/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8034 - Precision: 0.7112 - Recall: 0.4592 - accuracy: 0.5932 - loss: 0.8158 Epoch 5/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8206 - Precision: 0.7412 - Recall: 0.5103 - accuracy: 0.6055 - loss: 0.7740 Epoch 6/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8404 - Precision: 0.7600 - Recall: 0.5005 - accuracy: 0.6227 - loss: 0.7605 Epoch 7/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8470 - Precision: 0.7277 - Recall: 0.5222 - accuracy: 0.6555 - loss: 0.7228 Epoch 8/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8551 - Precision: 0.7250 - Recall: 0.5266 - accuracy: 0.6543 - loss: 0.7026 Epoch 9/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8652 - Precision: 0.7540 - Recall: 0.5242 - accuracy: 0.6535 - loss: 0.6755 Epoch 10/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8713 - Precision: 0.7699 - Recall: 0.5440 - accuracy: 0.6651 - loss: 0.6448 Epoch 11/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8772 - Precision: 0.7824 - Recall: 0.5846 - accuracy: 0.6770 - loss: 0.6638 Epoch 12/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8939 - Precision: 0.7544 - Recall: 0.5869 - accuracy: 0.6893 - loss: 0.5833 Epoch 13/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8967 - Precision: 0.7898 - Recall: 0.5979 - accuracy: 0.7318 - loss: 0.5973 Epoch 14/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8849 - Precision: 0.7425 - Recall: 0.5880 - accuracy: 0.6770 - loss: 0.6121 Epoch 15/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8832 - Precision: 0.7611 - Recall: 0.5696 - accuracy: 0.6689 - loss: 0.6198 Epoch 16/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8840 - Precision: 0.7541 - Recall: 0.5779 - accuracy: 0.6823 - loss: 0.6225 Epoch 17/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9111 - Precision: 0.7783 - Recall: 0.6457 - accuracy: 0.7336 - loss: 0.5477 Epoch 18/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8909 - Precision: 0.7428 - Recall: 0.6076 - accuracy: 0.6828 - loss: 0.5976 Epoch 19/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8984 - Precision: 0.8082 - Recall: 0.5927 - accuracy: 0.7148 - loss: 0.5879 Epoch 20/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9046 - Precision: 0.7611 - Recall: 0.6120 - accuracy: 0.7125 - loss: 0.5689 Epoch 21/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8943 - Precision: 0.7585 - Recall: 0.6044 - accuracy: 0.6754 - loss: 0.5856 Epoch 22/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8961 - Precision: 0.7621 - Recall: 0.6071 - accuracy: 0.7020 - loss: 0.5740 Epoch 23/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9107 - Precision: 0.7675 - Recall: 0.6368 - accuracy: 0.7200 - loss: 0.5491 Epoch 24/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9117 - Precision: 0.7892 - Recall: 0.6417 - accuracy: 0.7224 - loss: 0.5318 Epoch 25/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9161 - Precision: 0.7951 - Recall: 0.6624 - accuracy: 0.7320 - loss: 0.5351 Epoch 26/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9127 - Precision: 0.7905 - Recall: 0.6662 - accuracy: 0.7177 - loss: 0.5450 Epoch 27/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9236 - Precision: 0.8058 - Recall: 0.7005 - accuracy: 0.7466 - loss: 0.4929 Epoch 28/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8935 - Precision: 0.7476 - Recall: 0.5922 - accuracy: 0.6707 - loss: 0.5865 Epoch 29/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9164 - Precision: 0.7987 - Recall: 0.6662 - accuracy: 0.7245 - loss: 0.5236 Epoch 30/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9231 - Precision: 0.8041 - Recall: 0.6599 - accuracy: 0.7583 - loss: 0.5401 Epoch 31/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9208 - Precision: 0.8078 - Recall: 0.6557 - accuracy: 0.7537 - loss: 0.5394 Epoch 32/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9217 - Precision: 0.8097 - Recall: 0.6650 - accuracy: 0.7420 - loss: 0.5155 Epoch 33/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9215 - Precision: 0.8190 - Recall: 0.6328 - accuracy: 0.7360 - loss: 0.5170 Epoch 34/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9202 - Precision: 0.7853 - Recall: 0.6424 - accuracy: 0.7369 - loss: 0.5227 Epoch 35/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9254 - Precision: 0.7682 - Recall: 0.6549 - accuracy: 0.7412 - loss: 0.4795 Epoch 36/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9264 - Precision: 0.8050 - Recall: 0.6839 - accuracy: 0.7532 - loss: 0.4853 Epoch 37/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9174 - Precision: 0.7873 - Recall: 0.6308 - accuracy: 0.7405 - loss: 0.5248 Epoch 38/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9136 - Precision: 0.8023 - Recall: 0.6544 - accuracy: 0.7257 - loss: 0.5455 Epoch 39/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9240 - Precision: 0.8026 - Recall: 0.7093 - accuracy: 0.7472 - loss: 0.5153 Epoch 40/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9311 - Precision: 0.8192 - Recall: 0.7266 - accuracy: 0.7844 - loss: 0.4952 Epoch 41/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9143 - Precision: 0.7605 - Recall: 0.6728 - accuracy: 0.7111 - loss: 0.5399 Epoch 42/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9372 - Precision: 0.8207 - Recall: 0.7142 - accuracy: 0.7800 - loss: 0.4646 Epoch 43/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8934 - Precision: 0.7618 - Recall: 0.6718 - accuracy: 0.7185 - loss: 0.6255 Epoch 44/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9288 - Precision: 0.7988 - Recall: 0.6798 - accuracy: 0.7541 - loss: 0.4790 Epoch 45/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9314 - Precision: 0.8274 - Recall: 0.7017 - accuracy: 0.7581 - loss: 0.4770 Epoch 46/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9319 - Precision: 0.8143 - Recall: 0.7238 - accuracy: 0.7622 - loss: 0.4847 Epoch 47/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9409 - Precision: 0.8277 - Recall: 0.7318 - accuracy: 0.7998 - loss: 0.4429 Epoch 48/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9409 - Precision: 0.8384 - Recall: 0.7525 - accuracy: 0.7968 - loss: 0.4689 Epoch 49/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9291 - Precision: 0.8014 - Recall: 0.7039 - accuracy: 0.7604 - loss: 0.4856 Epoch 50/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9234 - Precision: 0.8060 - Recall: 0.6819 - accuracy: 0.7588 - loss: 0.5142 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step Epoch 1/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 5s 4ms/step - AUC: 0.6170 - Precision: 0.4674 - Recall: 0.3408 - accuracy: 0.4409 - loss: 1.3235 Epoch 2/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6264 - Precision: 0.5273 - Recall: 0.2886 - accuracy: 0.4949 - loss: 1.1669 Epoch 3/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6730 - Precision: 0.5537 - Recall: 0.2998 - accuracy: 0.4880 - loss: 1.0229 Epoch 4/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6626 - Precision: 0.6291 - Recall: 0.3022 - accuracy: 0.4823 - loss: 1.0432 Epoch 5/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7151 - Precision: 0.6591 - Recall: 0.3164 - accuracy: 0.5441 - loss: 0.9796 Epoch 6/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7461 - Precision: 0.7501 - Recall: 0.3412 - accuracy: 0.5554 - loss: 0.9409 Epoch 7/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7585 - Precision: 0.7780 - Recall: 0.3574 - accuracy: 0.5787 - loss: 0.8831 Epoch 8/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7947 - Precision: 0.7461 - Recall: 0.3994 - accuracy: 0.5784 - loss: 0.8354 Epoch 9/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7584 - Precision: 0.7797 - Recall: 0.3586 - accuracy: 0.5548 - loss: 0.8937 Epoch 10/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7930 - Precision: 0.7907 - Recall: 0.3749 - accuracy: 0.5892 - loss: 0.8213 Epoch 11/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.7982 - Precision: 0.7711 - Recall: 0.3871 - accuracy: 0.6018 - loss: 0.8160 Epoch 12/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8190 - Precision: 0.7922 - Recall: 0.4147 - accuracy: 0.6376 - loss: 0.8235 Epoch 13/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.7951 - Precision: 0.7938 - Recall: 0.3507 - accuracy: 0.5876 - loss: 0.8460 Epoch 14/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8317 - Precision: 0.8331 - Recall: 0.4138 - accuracy: 0.6456 - loss: 0.7565 Epoch 15/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8135 - Precision: 0.7762 - Recall: 0.4133 - accuracy: 0.6123 - loss: 0.8089 Epoch 16/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8049 - Precision: 0.7820 - Recall: 0.3917 - accuracy: 0.5878 - loss: 0.8056 Epoch 17/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8234 - Precision: 0.7931 - Recall: 0.4217 - accuracy: 0.5933 - loss: 0.7896 Epoch 18/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.7718 - Precision: 0.7358 - Recall: 0.3711 - accuracy: 0.5814 - loss: 0.8892 Epoch 19/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8260 - Precision: 0.7751 - Recall: 0.4125 - accuracy: 0.6222 - loss: 0.7575 Epoch 20/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8237 - Precision: 0.8422 - Recall: 0.4191 - accuracy: 0.6167 - loss: 0.7817 Epoch 21/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8386 - Precision: 0.8323 - Recall: 0.4192 - accuracy: 0.6051 - loss: 0.7875 Epoch 22/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8376 - Precision: 0.8051 - Recall: 0.4434 - accuracy: 0.6297 - loss: 0.7528 Epoch 23/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8295 - Precision: 0.7829 - Recall: 0.4342 - accuracy: 0.5979 - loss: 0.7534 Epoch 24/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8195 - Precision: 0.7677 - Recall: 0.3810 - accuracy: 0.6175 - loss: 0.8043 Epoch 25/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8160 - Precision: 0.7671 - Recall: 0.3861 - accuracy: 0.6154 - loss: 0.8057 Epoch 26/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8209 - Precision: 0.7796 - Recall: 0.3999 - accuracy: 0.6432 - loss: 0.7834 Epoch 27/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8087 - Precision: 0.7773 - Recall: 0.3867 - accuracy: 0.5892 - loss: 0.8162 Epoch 28/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8223 - Precision: 0.8126 - Recall: 0.3973 - accuracy: 0.6187 - loss: 0.8023 Epoch 29/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8376 - Precision: 0.7900 - Recall: 0.4106 - accuracy: 0.6372 - loss: 0.7496 Epoch 30/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8597 - Precision: 0.8599 - Recall: 0.4406 - accuracy: 0.6329 - loss: 0.6980 Epoch 31/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8342 - Precision: 0.8233 - Recall: 0.4478 - accuracy: 0.6084 - loss: 0.7588 Epoch 32/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8164 - Precision: 0.7630 - Recall: 0.3754 - accuracy: 0.5891 - loss: 0.7887 Epoch 33/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8432 - Precision: 0.7944 - Recall: 0.4440 - accuracy: 0.6260 - loss: 0.7441 Epoch 34/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8258 - Precision: 0.7531 - Recall: 0.4495 - accuracy: 0.6122 - loss: 0.7827 Epoch 35/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8569 - Precision: 0.8303 - Recall: 0.4550 - accuracy: 0.6562 - loss: 0.7197 Epoch 36/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8143 - Precision: 0.7868 - Recall: 0.4061 - accuracy: 0.5769 - loss: 0.7931 Epoch 37/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8424 - Precision: 0.7759 - Recall: 0.4485 - accuracy: 0.6224 - loss: 0.7275 Epoch 38/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8329 - Precision: 0.7985 - Recall: 0.4443 - accuracy: 0.6196 - loss: 0.7668 Epoch 39/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8458 - Precision: 0.7668 - Recall: 0.4302 - accuracy: 0.6449 - loss: 0.7331 Epoch 40/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8561 - Precision: 0.8308 - Recall: 0.4805 - accuracy: 0.6566 - loss: 0.7176 Epoch 41/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8426 - Precision: 0.7665 - Recall: 0.4592 - accuracy: 0.6453 - loss: 0.7497 Epoch 42/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8653 - Precision: 0.8253 - Recall: 0.4501 - accuracy: 0.6932 - loss: 0.7303 Epoch 43/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8178 - Precision: 0.7983 - Recall: 0.4009 - accuracy: 0.5939 - loss: 0.7917 Epoch 44/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8448 - Precision: 0.7896 - Recall: 0.4112 - accuracy: 0.6414 - loss: 0.7482 Epoch 45/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8246 - Precision: 0.8193 - Recall: 0.4061 - accuracy: 0.6365 - loss: 0.7774 Epoch 46/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8589 - Precision: 0.8659 - Recall: 0.4459 - accuracy: 0.6212 - loss: 0.7011 Epoch 47/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8408 - Precision: 0.8319 - Recall: 0.4459 - accuracy: 0.6305 - loss: 0.7629 Epoch 48/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8444 - Precision: 0.8311 - Recall: 0.4251 - accuracy: 0.6537 - loss: 0.7381 Epoch 49/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8298 - Precision: 0.7751 - Recall: 0.3971 - accuracy: 0.5928 - loss: 0.7847 Epoch 50/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8703 - Precision: 0.8372 - Recall: 0.4793 - accuracy: 0.6762 - loss: 0.6742 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step Epoch 1/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 4s 5ms/step - AUC: 0.4423 - Precision: 0.2933 - Recall: 0.2423 - accuracy: 0.2963 - loss: 2.1215 Epoch 2/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5391 - Precision: 0.3840 - Recall: 0.2421 - accuracy: 0.3732 - loss: 1.3337 Epoch 3/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5875 - Precision: 0.4356 - Recall: 0.2577 - accuracy: 0.4252 - loss: 1.2217 Epoch 4/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6106 - Precision: 0.4982 - Recall: 0.2673 - accuracy: 0.4144 - loss: 1.1273 Epoch 5/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.6555 - Precision: 0.6133 - Recall: 0.3257 - accuracy: 0.4695 - loss: 1.0761 Epoch 6/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6300 - Precision: 0.5103 - Recall: 0.2522 - accuracy: 0.4375 - loss: 1.0765 Epoch 7/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7182 - Precision: 0.6455 - Recall: 0.3350 - accuracy: 0.5169 - loss: 0.9831 Epoch 8/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.7234 - Precision: 0.6786 - Recall: 0.3612 - accuracy: 0.5258 - loss: 0.9360 Epoch 9/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7381 - Precision: 0.7239 - Recall: 0.3447 - accuracy: 0.5346 - loss: 0.9135 Epoch 10/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7525 - Precision: 0.7323 - Recall: 0.3645 - accuracy: 0.5471 - loss: 0.8868 Epoch 11/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7600 - Precision: 0.7420 - Recall: 0.3599 - accuracy: 0.5432 - loss: 0.8910 Epoch 12/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7580 - Precision: 0.7249 - Recall: 0.3845 - accuracy: 0.5602 - loss: 0.8739 Epoch 13/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8150 - Precision: 0.7927 - Recall: 0.4295 - accuracy: 0.6099 - loss: 0.8118 Epoch 14/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7873 - Precision: 0.7475 - Recall: 0.3950 - accuracy: 0.5645 - loss: 0.8399 Epoch 15/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8026 - Precision: 0.7289 - Recall: 0.3756 - accuracy: 0.5637 - loss: 0.8259 Epoch 16/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8136 - Precision: 0.7804 - Recall: 0.4106 - accuracy: 0.5851 - loss: 0.8079 Epoch 17/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8134 - Precision: 0.7442 - Recall: 0.4182 - accuracy: 0.5840 - loss: 0.8201 Epoch 18/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8264 - Precision: 0.7726 - Recall: 0.4397 - accuracy: 0.6102 - loss: 0.7869 Epoch 19/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8288 - Precision: 0.7287 - Recall: 0.4049 - accuracy: 0.6312 - loss: 0.7607 Epoch 20/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8455 - Precision: 0.7391 - Recall: 0.4261 - accuracy: 0.6323 - loss: 0.7304 Epoch 21/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8153 - Precision: 0.7428 - Recall: 0.4069 - accuracy: 0.6051 - loss: 0.7888 Epoch 22/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8450 - Precision: 0.7466 - Recall: 0.4686 - accuracy: 0.6423 - loss: 0.7118 Epoch 23/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8604 - Precision: 0.7983 - Recall: 0.5147 - accuracy: 0.6745 - loss: 0.7093 Epoch 24/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8434 - Precision: 0.7601 - Recall: 0.4587 - accuracy: 0.6442 - loss: 0.7421 Epoch 25/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8554 - Precision: 0.7960 - Recall: 0.4993 - accuracy: 0.6517 - loss: 0.7247 Epoch 26/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8644 - Precision: 0.7737 - Recall: 0.4894 - accuracy: 0.6435 - loss: 0.6851 Epoch 27/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8633 - Precision: 0.8124 - Recall: 0.4907 - accuracy: 0.6531 - loss: 0.6847 Epoch 28/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8740 - Precision: 0.7894 - Recall: 0.5026 - accuracy: 0.6907 - loss: 0.6847 Epoch 29/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8731 - Precision: 0.8150 - Recall: 0.4817 - accuracy: 0.6352 - loss: 0.6458 Epoch 30/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8569 - Precision: 0.7939 - Recall: 0.4903 - accuracy: 0.6439 - loss: 0.6975 Epoch 31/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8657 - Precision: 0.7652 - Recall: 0.4801 - accuracy: 0.6585 - loss: 0.6620 Epoch 32/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8684 - Precision: 0.7579 - Recall: 0.4938 - accuracy: 0.6588 - loss: 0.6595 Epoch 33/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8600 - Precision: 0.7996 - Recall: 0.5020 - accuracy: 0.6760 - loss: 0.7517 Epoch 34/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8437 - Precision: 0.7545 - Recall: 0.4910 - accuracy: 0.6244 - loss: 0.7884 Epoch 35/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8574 - Precision: 0.7768 - Recall: 0.4982 - accuracy: 0.6383 - loss: 0.7010 Epoch 36/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8751 - Precision: 0.7588 - Recall: 0.5175 - accuracy: 0.6617 - loss: 0.6398 Epoch 37/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8686 - Precision: 0.7625 - Recall: 0.5305 - accuracy: 0.6711 - loss: 0.6785 Epoch 38/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8663 - Precision: 0.7863 - Recall: 0.5219 - accuracy: 0.6594 - loss: 0.6843 Epoch 39/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8937 - Precision: 0.8586 - Recall: 0.5330 - accuracy: 0.6860 - loss: 0.5941 Epoch 40/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8685 - Precision: 0.7592 - Recall: 0.5105 - accuracy: 0.6496 - loss: 0.6728 Epoch 41/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8743 - Precision: 0.7804 - Recall: 0.4974 - accuracy: 0.6620 - loss: 0.6361 Epoch 42/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8723 - Precision: 0.8073 - Recall: 0.5430 - accuracy: 0.6867 - loss: 0.6802 Epoch 43/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8764 - Precision: 0.8068 - Recall: 0.5004 - accuracy: 0.6672 - loss: 0.6584 Epoch 44/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9007 - Precision: 0.8082 - Recall: 0.5550 - accuracy: 0.6902 - loss: 0.5961 Epoch 45/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8783 - Precision: 0.8100 - Recall: 0.5271 - accuracy: 0.6737 - loss: 0.6490 Epoch 46/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8613 - Precision: 0.7800 - Recall: 0.4997 - accuracy: 0.6495 - loss: 0.6982 Epoch 47/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8805 - Precision: 0.7965 - Recall: 0.5126 - accuracy: 0.6720 - loss: 0.6448 Epoch 48/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8851 - Precision: 0.8029 - Recall: 0.5266 - accuracy: 0.6691 - loss: 0.6078 Epoch 49/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8892 - Precision: 0.7884 - Recall: 0.5237 - accuracy: 0.6987 - loss: 0.6091 Epoch 50/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8596 - Precision: 0.7365 - Recall: 0.5130 - accuracy: 0.6447 - loss: 0.7022 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step Epoch 1/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 4s 5ms/step - AUC: 0.4859 - Precision: 0.2868 - Recall: 0.1893 - accuracy: 0.3087 - loss: 1.4429 Epoch 2/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5943 - Precision: 0.4308 - Recall: 0.2108 - accuracy: 0.3989 - loss: 1.1731 Epoch 3/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6257 - Precision: 0.5284 - Recall: 0.2551 - accuracy: 0.4574 - loss: 1.0946 Epoch 4/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6442 - Precision: 0.5599 - Recall: 0.2498 - accuracy: 0.4548 - loss: 1.0909 Epoch 5/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6304 - Precision: 0.5429 - Recall: 0.2650 - accuracy: 0.4656 - loss: 1.0860 Epoch 6/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7133 - Precision: 0.6869 - Recall: 0.3296 - accuracy: 0.5408 - loss: 0.9811 Epoch 7/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7272 - Precision: 0.7034 - Recall: 0.3652 - accuracy: 0.5441 - loss: 0.9547 Epoch 8/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6952 - Precision: 0.6557 - Recall: 0.3156 - accuracy: 0.5208 - loss: 0.9719 Epoch 9/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7145 - Precision: 0.6644 - Recall: 0.2911 - accuracy: 0.5161 - loss: 0.9565 Epoch 10/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7487 - Precision: 0.7159 - Recall: 0.3336 - accuracy: 0.5729 - loss: 0.9171 Epoch 11/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7371 - Precision: 0.7421 - Recall: 0.3393 - accuracy: 0.5180 - loss: 0.9363 Epoch 12/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7441 - Precision: 0.7172 - Recall: 0.3590 - accuracy: 0.5407 - loss: 0.9164 Epoch 13/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7931 - Precision: 0.7543 - Recall: 0.4173 - accuracy: 0.5988 - loss: 0.8358 Epoch 14/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7865 - Precision: 0.7505 - Recall: 0.3853 - accuracy: 0.5576 - loss: 0.8422 Epoch 15/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8034 - Precision: 0.8131 - Recall: 0.4314 - accuracy: 0.5954 - loss: 0.8124 Epoch 16/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8016 - Precision: 0.7389 - Recall: 0.3898 - accuracy: 0.5690 - loss: 0.7924 Epoch 17/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8334 - Precision: 0.8094 - Recall: 0.4273 - accuracy: 0.6102 - loss: 0.7351 Epoch 18/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8206 - Precision: 0.7773 - Recall: 0.4254 - accuracy: 0.5927 - loss: 0.7567 Epoch 19/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8455 - Precision: 0.7837 - Recall: 0.4609 - accuracy: 0.6183 - loss: 0.7075 Epoch 20/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8334 - Precision: 0.7973 - Recall: 0.4880 - accuracy: 0.6278 - loss: 0.7623 Epoch 21/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8380 - Precision: 0.7796 - Recall: 0.4526 - accuracy: 0.6115 - loss: 0.7400 Epoch 22/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8386 - Precision: 0.8089 - Recall: 0.4349 - accuracy: 0.6280 - loss: 0.7514 Epoch 23/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8553 - Precision: 0.7981 - Recall: 0.4663 - accuracy: 0.6370 - loss: 0.7137 Epoch 24/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8383 - Precision: 0.7808 - Recall: 0.4469 - accuracy: 0.6457 - loss: 0.7391 Epoch 25/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8527 - Precision: 0.8247 - Recall: 0.4834 - accuracy: 0.6265 - loss: 0.7044 Epoch 26/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8508 - Precision: 0.7940 - Recall: 0.4795 - accuracy: 0.6105 - loss: 0.7150 Epoch 27/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8570 - Precision: 0.8216 - Recall: 0.4939 - accuracy: 0.6437 - loss: 0.6963 Epoch 28/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8290 - Precision: 0.7362 - Recall: 0.4703 - accuracy: 0.6079 - loss: 0.7681 Epoch 29/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8747 - Precision: 0.8205 - Recall: 0.4895 - accuracy: 0.6362 - loss: 0.6566 Epoch 30/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8633 - Precision: 0.7968 - Recall: 0.4959 - accuracy: 0.6320 - loss: 0.6516 Epoch 31/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8605 - Precision: 0.7903 - Recall: 0.4867 - accuracy: 0.6498 - loss: 0.6918 Epoch 32/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8728 - Precision: 0.7984 - Recall: 0.5148 - accuracy: 0.6617 - loss: 0.6690 Epoch 33/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8768 - Precision: 0.8148 - Recall: 0.5183 - accuracy: 0.7112 - loss: 0.7215 Epoch 34/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8663 - Precision: 0.7680 - Recall: 0.4778 - accuracy: 0.6137 - loss: 0.6672 Epoch 35/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8617 - Precision: 0.7667 - Recall: 0.4904 - accuracy: 0.6491 - loss: 0.6844 Epoch 36/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8741 - Precision: 0.7693 - Recall: 0.5012 - accuracy: 0.6654 - loss: 0.6707 Epoch 37/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8738 - Precision: 0.7832 - Recall: 0.4999 - accuracy: 0.6645 - loss: 0.6619 Epoch 38/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8649 - Precision: 0.7855 - Recall: 0.4662 - accuracy: 0.6439 - loss: 0.6695 Epoch 39/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8782 - Precision: 0.8116 - Recall: 0.4811 - accuracy: 0.6845 - loss: 0.6404 Epoch 40/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8919 - Precision: 0.7753 - Recall: 0.5141 - accuracy: 0.6813 - loss: 0.6029 Epoch 41/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8556 - Precision: 0.7501 - Recall: 0.4891 - accuracy: 0.6686 - loss: 0.7485 Epoch 42/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8824 - Precision: 0.8017 - Recall: 0.5215 - accuracy: 0.6691 - loss: 0.6264 Epoch 43/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8997 - Precision: 0.7869 - Recall: 0.5208 - accuracy: 0.6811 - loss: 0.5780 Epoch 44/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8843 - Precision: 0.8174 - Recall: 0.5372 - accuracy: 0.6569 - loss: 0.6136 Epoch 45/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8893 - Precision: 0.8009 - Recall: 0.5549 - accuracy: 0.7069 - loss: 0.6137 Epoch 46/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8901 - Precision: 0.7959 - Recall: 0.5572 - accuracy: 0.6744 - loss: 0.6103 Epoch 47/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8825 - Precision: 0.7971 - Recall: 0.5260 - accuracy: 0.6943 - loss: 0.6115 Epoch 48/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9056 - Precision: 0.8212 - Recall: 0.5726 - accuracy: 0.7022 - loss: 0.5757 Epoch 49/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8857 - Precision: 0.7777 - Recall: 0.5455 - accuracy: 0.6757 - loss: 0.6569 Epoch 50/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8857 - Precision: 0.8173 - Recall: 0.5209 - accuracy: 0.6976 - loss: 0.6217 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 27ms/step Epoch 1/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 4s 4ms/step - AUC: 0.4788 - Precision: 0.3106 - Recall: 0.2588 - accuracy: 0.3344 - loss: 3.4376 Epoch 2/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5251 - Precision: 0.3672 - Recall: 0.2702 - accuracy: 0.3468 - loss: 2.0949 Epoch 3/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.5684 - Precision: 0.4074 - Recall: 0.2612 - accuracy: 0.4021 - loss: 1.5617 Epoch 4/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5633 - Precision: 0.4320 - Recall: 0.2744 - accuracy: 0.4130 - loss: 1.5164 Epoch 5/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5648 - Precision: 0.4359 - Recall: 0.2532 - accuracy: 0.4165 - loss: 1.5005 Epoch 6/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5692 - Precision: 0.4039 - Recall: 0.2227 - accuracy: 0.4140 - loss: 1.3130 Epoch 7/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5655 - Precision: 0.3732 - Recall: 0.1605 - accuracy: 0.4326 - loss: 1.3047 Epoch 8/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6134 - Precision: 0.4229 - Recall: 0.1935 - accuracy: 0.4773 - loss: 1.1404 Epoch 9/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6186 - Precision: 0.4355 - Recall: 0.1861 - accuracy: 0.4598 - loss: 1.1102 Epoch 10/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5547 - Precision: 0.3682 - Recall: 0.1262 - accuracy: 0.4264 - loss: 1.2085 Epoch 11/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6066 - Precision: 0.4633 - Recall: 0.1971 - accuracy: 0.4471 - loss: 1.1283 Epoch 12/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6126 - Precision: 0.4478 - Recall: 0.1929 - accuracy: 0.4826 - loss: 1.1202 Epoch 13/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6294 - Precision: 0.5069 - Recall: 0.1629 - accuracy: 0.4888 - loss: 1.1032 Epoch 14/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5538 - Precision: 0.3754 - Recall: 0.1215 - accuracy: 0.4066 - loss: 1.1684 Epoch 15/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6388 - Precision: 0.5367 - Recall: 0.2047 - accuracy: 0.4992 - loss: 1.0604 Epoch 16/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6111 - Precision: 0.4824 - Recall: 0.1818 - accuracy: 0.4561 - loss: 1.0939 Epoch 17/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6137 - Precision: 0.4361 - Recall: 0.1248 - accuracy: 0.4790 - loss: 1.0943 Epoch 18/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6040 - Precision: 0.4929 - Recall: 0.1563 - accuracy: 0.5050 - loss: 1.0948 Epoch 19/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6194 - Precision: 0.4257 - Recall: 0.1177 - accuracy: 0.4749 - loss: 1.0810 Epoch 20/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6082 - Precision: 0.4785 - Recall: 0.1463 - accuracy: 0.4658 - loss: 1.0974 Epoch 21/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.5975 - Precision: 0.4915 - Recall: 0.1646 - accuracy: 0.4572 - loss: 1.1039 Epoch 22/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6301 - Precision: 0.5467 - Recall: 0.1576 - accuracy: 0.4934 - loss: 1.0579 Epoch 23/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5855 - Precision: 0.4138 - Recall: 0.1078 - accuracy: 0.4632 - loss: 1.1147 Epoch 24/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.6111 - Precision: 0.5036 - Recall: 0.1269 - accuracy: 0.4842 - loss: 1.0666 Epoch 25/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6223 - Precision: 0.4711 - Recall: 0.1458 - accuracy: 0.4727 - loss: 1.0767 Epoch 26/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6337 - Precision: 0.4913 - Recall: 0.1716 - accuracy: 0.5161 - loss: 1.0806 Epoch 27/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6625 - Precision: 0.5639 - Recall: 0.1814 - accuracy: 0.5276 - loss: 1.0262 Epoch 28/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6345 - Precision: 0.5261 - Recall: 0.1304 - accuracy: 0.4916 - loss: 1.0429 Epoch 29/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6080 - Precision: 0.5031 - Recall: 0.1366 - accuracy: 0.4740 - loss: 1.0747 Epoch 30/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6336 - Precision: 0.4762 - Recall: 0.1108 - accuracy: 0.5168 - loss: 1.0720 Epoch 31/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6235 - Precision: 0.4911 - Recall: 0.1329 - accuracy: 0.5020 - loss: 1.0566 Epoch 32/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6132 - Precision: 0.4356 - Recall: 0.1293 - accuracy: 0.4820 - loss: 1.0622 Epoch 33/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6239 - Precision: 0.5276 - Recall: 0.1837 - accuracy: 0.4723 - loss: 1.0707 Epoch 34/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6332 - Precision: 0.4980 - Recall: 0.1544 - accuracy: 0.5000 - loss: 1.0474 Epoch 35/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6560 - Precision: 0.6655 - Recall: 0.1632 - accuracy: 0.5129 - loss: 1.0170 Epoch 36/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6067 - Precision: 0.4787 - Recall: 0.1725 - accuracy: 0.4637 - loss: 1.0628 Epoch 37/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6105 - Precision: 0.5024 - Recall: 0.1551 - accuracy: 0.4884 - loss: 1.0558 Epoch 38/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6640 - Precision: 0.6219 - Recall: 0.2368 - accuracy: 0.4970 - loss: 1.0245 Epoch 39/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.6357 - Precision: 0.5517 - Recall: 0.1350 - accuracy: 0.5144 - loss: 1.0464 Epoch 40/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6675 - Precision: 0.6592 - Recall: 0.2166 - accuracy: 0.5155 - loss: 1.0248 Epoch 41/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6638 - Precision: 0.5889 - Recall: 0.1692 - accuracy: 0.5104 - loss: 1.0267 Epoch 42/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6428 - Precision: 0.6511 - Recall: 0.1525 - accuracy: 0.4782 - loss: 1.0271 Epoch 43/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6381 - Precision: 0.5646 - Recall: 0.1546 - accuracy: 0.4955 - loss: 1.0589 Epoch 44/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6584 - Precision: 0.6201 - Recall: 0.1714 - accuracy: 0.4905 - loss: 1.0159 Epoch 45/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6427 - Precision: 0.5831 - Recall: 0.2118 - accuracy: 0.4789 - loss: 1.0424 Epoch 46/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6356 - Precision: 0.5890 - Recall: 0.1668 - accuracy: 0.4894 - loss: 1.0337 Epoch 47/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6708 - Precision: 0.6530 - Recall: 0.2212 - accuracy: 0.4940 - loss: 1.0014 Epoch 48/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6777 - Precision: 0.6574 - Recall: 0.2400 - accuracy: 0.4897 - loss: 1.0030 Epoch 49/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6920 - Precision: 0.6666 - Recall: 0.2292 - accuracy: 0.5176 - loss: 0.9820 Epoch 50/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6992 - Precision: 0.7359 - Recall: 0.2762 - accuracy: 0.5005 - loss: 0.9544 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step Epoch 1/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 4s 4ms/step - AUC: 0.5266 - Precision: 0.3601 - Recall: 0.3260 - accuracy: 0.3525 - loss: 4.1864 Epoch 2/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.4587 - Precision: 0.2910 - Recall: 0.2348 - accuracy: 0.2992 - loss: 2.9254 Epoch 3/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5052 - Precision: 0.3139 - Recall: 0.2177 - accuracy: 0.3226 - loss: 1.9989 Epoch 4/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5566 - Precision: 0.4041 - Recall: 0.2703 - accuracy: 0.3955 - loss: 1.7828 Epoch 5/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5676 - Precision: 0.4244 - Recall: 0.2701 - accuracy: 0.3955 - loss: 1.4747 Epoch 6/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5771 - Precision: 0.4581 - Recall: 0.2955 - accuracy: 0.3935 - loss: 1.3845 Epoch 7/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6285 - Precision: 0.4837 - Recall: 0.2573 - accuracy: 0.4875 - loss: 1.3114 Epoch 8/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6024 - Precision: 0.4700 - Recall: 0.2241 - accuracy: 0.4571 - loss: 1.2845 Epoch 9/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5711 - Precision: 0.4116 - Recall: 0.2173 - accuracy: 0.4146 - loss: 1.2662 Epoch 10/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6039 - Precision: 0.4693 - Recall: 0.2435 - accuracy: 0.4573 - loss: 1.2054 Epoch 11/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6185 - Precision: 0.5255 - Recall: 0.2453 - accuracy: 0.4615 - loss: 1.1356 Epoch 12/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5530 - Precision: 0.3851 - Recall: 0.1686 - accuracy: 0.4190 - loss: 1.2441 Epoch 13/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5950 - Precision: 0.4399 - Recall: 0.1856 - accuracy: 0.4736 - loss: 1.1558 Epoch 14/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5842 - Precision: 0.4437 - Recall: 0.1810 - accuracy: 0.4417 - loss: 1.1654 Epoch 15/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6054 - Precision: 0.4712 - Recall: 0.1933 - accuracy: 0.4552 - loss: 1.1208 Epoch 16/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5977 - Precision: 0.4184 - Recall: 0.1583 - accuracy: 0.4668 - loss: 1.1354 Epoch 17/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6285 - Precision: 0.5404 - Recall: 0.1881 - accuracy: 0.5021 - loss: 1.0874 Epoch 18/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6665 - Precision: 0.5572 - Recall: 0.2233 - accuracy: 0.5216 - loss: 1.0252 Epoch 19/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5930 - Precision: 0.4251 - Recall: 0.1602 - accuracy: 0.4634 - loss: 1.1322 Epoch 20/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6037 - Precision: 0.4656 - Recall: 0.1893 - accuracy: 0.4764 - loss: 1.1020 Epoch 21/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6080 - Precision: 0.4962 - Recall: 0.1555 - accuracy: 0.4687 - loss: 1.0789 Epoch 22/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6021 - Precision: 0.4944 - Recall: 0.1910 - accuracy: 0.4688 - loss: 1.0779 Epoch 23/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6318 - Precision: 0.5336 - Recall: 0.1853 - accuracy: 0.4832 - loss: 1.0655 Epoch 24/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6257 - Precision: 0.5037 - Recall: 0.1791 - accuracy: 0.4654 - loss: 1.0653 Epoch 25/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5880 - Precision: 0.4398 - Recall: 0.1397 - accuracy: 0.4318 - loss: 1.1067 Epoch 26/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6438 - Precision: 0.5670 - Recall: 0.2235 - accuracy: 0.4798 - loss: 1.0420 Epoch 27/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6330 - Precision: 0.5518 - Recall: 0.2064 - accuracy: 0.4955 - loss: 1.0582 Epoch 28/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6013 - Precision: 0.4783 - Recall: 0.1375 - accuracy: 0.4810 - loss: 1.0718 Epoch 29/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6252 - Precision: 0.5778 - Recall: 0.1808 - accuracy: 0.4615 - loss: 1.0630 Epoch 30/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6222 - Precision: 0.5040 - Recall: 0.1975 - accuracy: 0.4591 - loss: 1.0633 Epoch 31/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6241 - Precision: 0.5470 - Recall: 0.1667 - accuracy: 0.4939 - loss: 1.0524 Epoch 32/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5817 - Precision: 0.3981 - Recall: 0.1114 - accuracy: 0.4619 - loss: 1.0900 Epoch 33/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6403 - Precision: 0.5573 - Recall: 0.1373 - accuracy: 0.5007 - loss: 1.0467 Epoch 34/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6229 - Precision: 0.5180 - Recall: 0.1618 - accuracy: 0.4677 - loss: 1.0488 Epoch 35/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6147 - Precision: 0.5210 - Recall: 0.1331 - accuracy: 0.4784 - loss: 1.0646 Epoch 36/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6295 - Precision: 0.5758 - Recall: 0.1526 - accuracy: 0.4790 - loss: 1.0588 Epoch 37/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6294 - Precision: 0.4964 - Recall: 0.1865 - accuracy: 0.4903 - loss: 1.0605 Epoch 38/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6000 - Precision: 0.5375 - Recall: 0.1561 - accuracy: 0.4796 - loss: 1.0715 Epoch 39/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6604 - Precision: 0.5828 - Recall: 0.2018 - accuracy: 0.5154 - loss: 1.0249 Epoch 40/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6045 - Precision: 0.4729 - Recall: 0.1347 - accuracy: 0.4997 - loss: 1.0636 Epoch 41/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6128 - Precision: 0.5012 - Recall: 0.1104 - accuracy: 0.4660 - loss: 1.0695 Epoch 42/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6259 - Precision: 0.5150 - Recall: 0.1894 - accuracy: 0.4993 - loss: 1.0567 Epoch 43/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6419 - Precision: 0.5451 - Recall: 0.2032 - accuracy: 0.4866 - loss: 1.0365 Epoch 44/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6475 - Precision: 0.5669 - Recall: 0.2133 - accuracy: 0.5147 - loss: 1.0312 Epoch 45/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6175 - Precision: 0.5442 - Recall: 0.1839 - accuracy: 0.4652 - loss: 1.0570 Epoch 46/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6059 - Precision: 0.4787 - Recall: 0.1703 - accuracy: 0.4754 - loss: 1.0625 Epoch 47/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6573 - Precision: 0.5945 - Recall: 0.2144 - accuracy: 0.5285 - loss: 1.0237 Epoch 48/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6431 - Precision: 0.5504 - Recall: 0.1796 - accuracy: 0.5150 - loss: 1.0266 Epoch 49/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6577 - Precision: 0.5793 - Recall: 0.2104 - accuracy: 0.5255 - loss: 1.0207 Epoch 50/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6270 - Precision: 0.5357 - Recall: 0.1430 - accuracy: 0.4812 - loss: 1.0438 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 43ms/step Epoch 1/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 6s 5ms/step - AUC: 0.4536 - Precision: 0.2584 - Recall: 0.2272 - accuracy: 0.2788 - loss: 4.9837 Epoch 2/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5171 - Precision: 0.3257 - Recall: 0.2724 - accuracy: 0.3236 - loss: 3.0947 Epoch 3/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5076 - Precision: 0.3473 - Recall: 0.2911 - accuracy: 0.3522 - loss: 2.7684 Epoch 4/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5767 - Precision: 0.3967 - Recall: 0.3305 - accuracy: 0.3927 - loss: 2.1010 Epoch 5/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.5320 - Precision: 0.3778 - Recall: 0.2759 - accuracy: 0.3751 - loss: 1.9529 Epoch 6/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5503 - Precision: 0.4021 - Recall: 0.3051 - accuracy: 0.3838 - loss: 2.0298 Epoch 7/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.5551 - Precision: 0.3913 - Recall: 0.2862 - accuracy: 0.3762 - loss: 1.8280 Epoch 8/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5753 - Precision: 0.4273 - Recall: 0.2909 - accuracy: 0.4221 - loss: 1.4770 Epoch 9/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5573 - Precision: 0.3655 - Recall: 0.2247 - accuracy: 0.3789 - loss: 1.5277 Epoch 10/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5667 - Precision: 0.3962 - Recall: 0.2301 - accuracy: 0.4055 - loss: 1.4553 Epoch 11/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5339 - Precision: 0.3695 - Recall: 0.2250 - accuracy: 0.3709 - loss: 1.4424 Epoch 12/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5853 - Precision: 0.4486 - Recall: 0.2243 - accuracy: 0.4294 - loss: 1.2468 Epoch 13/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6130 - Precision: 0.4523 - Recall: 0.2282 - accuracy: 0.4373 - loss: 1.1891 Epoch 14/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6040 - Precision: 0.4501 - Recall: 0.2174 - accuracy: 0.4345 - loss: 1.1953 Epoch 15/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5445 - Precision: 0.3814 - Recall: 0.1572 - accuracy: 0.3794 - loss: 1.2868 Epoch 16/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6056 - Precision: 0.5187 - Recall: 0.2236 - accuracy: 0.4652 - loss: 1.1604 Epoch 17/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5810 - Precision: 0.5169 - Recall: 0.2252 - accuracy: 0.4465 - loss: 1.1878 Epoch 18/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6078 - Precision: 0.4603 - Recall: 0.1901 - accuracy: 0.4500 - loss: 1.1453 Epoch 19/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5870 - Precision: 0.4597 - Recall: 0.1857 - accuracy: 0.4597 - loss: 1.2161 Epoch 20/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5944 - Precision: 0.4647 - Recall: 0.2003 - accuracy: 0.4588 - loss: 1.1683 Epoch 21/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6151 - Precision: 0.5267 - Recall: 0.2009 - accuracy: 0.4535 - loss: 1.1430 Epoch 22/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6427 - Precision: 0.5210 - Recall: 0.2097 - accuracy: 0.4878 - loss: 1.0916 Epoch 23/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6289 - Precision: 0.5239 - Recall: 0.2369 - accuracy: 0.4733 - loss: 1.1022 Epoch 24/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6050 - Precision: 0.4489 - Recall: 0.1839 - accuracy: 0.4155 - loss: 1.1121 Epoch 25/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6171 - Precision: 0.4915 - Recall: 0.2215 - accuracy: 0.4422 - loss: 1.0979 Epoch 26/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6069 - Precision: 0.4804 - Recall: 0.1756 - accuracy: 0.4663 - loss: 1.1169 Epoch 27/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6132 - Precision: 0.5338 - Recall: 0.1997 - accuracy: 0.4377 - loss: 1.1161 Epoch 28/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6030 - Precision: 0.5368 - Recall: 0.2394 - accuracy: 0.4396 - loss: 1.1474 Epoch 29/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5895 - Precision: 0.3978 - Recall: 0.1549 - accuracy: 0.4314 - loss: 1.1233 Epoch 30/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5996 - Precision: 0.4723 - Recall: 0.1649 - accuracy: 0.4328 - loss: 1.1176 Epoch 31/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6296 - Precision: 0.5477 - Recall: 0.1737 - accuracy: 0.4951 - loss: 1.0709 Epoch 32/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6179 - Precision: 0.5609 - Recall: 0.1958 - accuracy: 0.4623 - loss: 1.0940 Epoch 33/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6105 - Precision: 0.5092 - Recall: 0.1932 - accuracy: 0.4445 - loss: 1.1028 Epoch 34/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6112 - Precision: 0.5486 - Recall: 0.1943 - accuracy: 0.4429 - loss: 1.0868 Epoch 35/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6211 - Precision: 0.4652 - Recall: 0.1787 - accuracy: 0.4896 - loss: 1.1147 Epoch 36/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6161 - Precision: 0.5055 - Recall: 0.1836 - accuracy: 0.4793 - loss: 1.0821 Epoch 37/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6589 - Precision: 0.5854 - Recall: 0.2231 - accuracy: 0.4855 - loss: 1.0343 Epoch 38/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6004 - Precision: 0.5353 - Recall: 0.1827 - accuracy: 0.4107 - loss: 1.0990 Epoch 39/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6325 - Precision: 0.4721 - Recall: 0.1715 - accuracy: 0.4996 - loss: 1.0697 Epoch 40/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6705 - Precision: 0.6280 - Recall: 0.1999 - accuracy: 0.5196 - loss: 1.0187 Epoch 41/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6410 - Precision: 0.5111 - Recall: 0.1326 - accuracy: 0.4704 - loss: 1.0643 Epoch 42/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6166 - Precision: 0.4720 - Recall: 0.1725 - accuracy: 0.4640 - loss: 1.0795 Epoch 43/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6514 - Precision: 0.5813 - Recall: 0.2199 - accuracy: 0.4962 - loss: 1.0363 Epoch 44/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6292 - Precision: 0.5844 - Recall: 0.2093 - accuracy: 0.4962 - loss: 1.0529 Epoch 45/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6189 - Precision: 0.5687 - Recall: 0.1589 - accuracy: 0.4638 - loss: 1.0698 Epoch 46/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6420 - Precision: 0.5787 - Recall: 0.1828 - accuracy: 0.5106 - loss: 1.0599 Epoch 47/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6260 - Precision: 0.5371 - Recall: 0.1700 - accuracy: 0.5210 - loss: 1.0574 Epoch 48/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6846 - Precision: 0.6497 - Recall: 0.2557 - accuracy: 0.5065 - loss: 1.0111 Epoch 49/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6628 - Precision: 0.5825 - Recall: 0.2338 - accuracy: 0.5086 - loss: 1.0247 Epoch 50/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6393 - Precision: 0.5805 - Recall: 0.2243 - accuracy: 0.4822 - loss: 1.0493 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 32ms/step Epoch 1/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 4s 4ms/step - AUC: 0.6710 - Precision: 0.5363 - Recall: 0.2895 - accuracy: 0.4543 - loss: 1.1222 Epoch 2/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7924 - Precision: 0.7329 - Recall: 0.3794 - accuracy: 0.5931 - loss: 0.8486 Epoch 3/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7678 - Precision: 0.6904 - Recall: 0.3587 - accuracy: 0.5607 - loss: 0.9036 Epoch 4/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7886 - Precision: 0.7464 - Recall: 0.3772 - accuracy: 0.5941 - loss: 0.8546 Epoch 5/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7783 - Precision: 0.7788 - Recall: 0.3776 - accuracy: 0.5481 - loss: 0.8468 Epoch 6/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7755 - Precision: 0.8398 - Recall: 0.3354 - accuracy: 0.5659 - loss: 0.9422 Epoch 7/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7815 - Precision: 0.7624 - Recall: 0.3415 - accuracy: 0.5584 - loss: 0.8531 Epoch 8/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8177 - Precision: 0.7940 - Recall: 0.3821 - accuracy: 0.6192 - loss: 0.9072 Epoch 9/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8063 - Precision: 0.8467 - Recall: 0.3390 - accuracy: 0.5922 - loss: 0.8252 Epoch 10/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7859 - Precision: 0.7397 - Recall: 0.3883 - accuracy: 0.5716 - loss: 0.9559 Epoch 11/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8385 - Precision: 0.8391 - Recall: 0.4402 - accuracy: 0.6610 - loss: 0.7775 Epoch 12/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8197 - Precision: 0.7846 - Recall: 0.4078 - accuracy: 0.6241 - loss: 0.8529 Epoch 13/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7754 - Precision: 0.7672 - Recall: 0.2615 - accuracy: 0.5832 - loss: 0.9623 Epoch 14/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7896 - Precision: 0.7744 - Recall: 0.3659 - accuracy: 0.5626 - loss: 0.8401 Epoch 15/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.8361 - Precision: 0.7903 - Recall: 0.4179 - accuracy: 0.6409 - loss: 0.7698 Epoch 16/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8150 - Precision: 0.8314 - Recall: 0.4033 - accuracy: 0.5966 - loss: 0.7980 Epoch 17/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8203 - Precision: 0.8129 - Recall: 0.4109 - accuracy: 0.5856 - loss: 0.8142 Epoch 18/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7996 - Precision: 0.7852 - Recall: 0.3690 - accuracy: 0.5740 - loss: 0.8503 Epoch 19/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7928 - Precision: 0.7900 - Recall: 0.3304 - accuracy: 0.5704 - loss: 0.8519 Epoch 20/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.8322 - Precision: 0.8252 - Recall: 0.4465 - accuracy: 0.6370 - loss: 0.7646 Epoch 21/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8123 - Precision: 0.8123 - Recall: 0.3732 - accuracy: 0.6175 - loss: 0.8204 Epoch 22/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8299 - Precision: 0.7884 - Recall: 0.3958 - accuracy: 0.6270 - loss: 0.7845 Epoch 23/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8147 - Precision: 0.7437 - Recall: 0.3957 - accuracy: 0.5806 - loss: 0.8160 Epoch 24/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7805 - Precision: 0.8077 - Recall: 0.3227 - accuracy: 0.5417 - loss: 0.8339 Epoch 25/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7965 - Precision: 0.7533 - Recall: 0.3840 - accuracy: 0.5654 - loss: 0.8254 Epoch 26/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8278 - Precision: 0.7729 - Recall: 0.4305 - accuracy: 0.6208 - loss: 0.7839 Epoch 27/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7916 - Precision: 0.7163 - Recall: 0.3533 - accuracy: 0.5704 - loss: 0.9116 Epoch 28/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8216 - Precision: 0.7889 - Recall: 0.4169 - accuracy: 0.5981 - loss: 0.7863 Epoch 29/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8039 - Precision: 0.7262 - Recall: 0.4204 - accuracy: 0.5730 - loss: 0.8324 Epoch 30/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7879 - Precision: 0.7902 - Recall: 0.3389 - accuracy: 0.5906 - loss: 0.9412 Epoch 31/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8143 - Precision: 0.8097 - Recall: 0.3937 - accuracy: 0.6060 - loss: 0.7951 Epoch 32/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8079 - Precision: 0.7256 - Recall: 0.3942 - accuracy: 0.5928 - loss: 0.8825 Epoch 33/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8188 - Precision: 0.7680 - Recall: 0.4077 - accuracy: 0.5920 - loss: 0.8285 Epoch 34/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8217 - Precision: 0.7975 - Recall: 0.3931 - accuracy: 0.5783 - loss: 0.8115 Epoch 35/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8012 - Precision: 0.7769 - Recall: 0.4433 - accuracy: 0.6025 - loss: 0.8367 Epoch 36/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8159 - Precision: 0.7260 - Recall: 0.4244 - accuracy: 0.6245 - loss: 0.9376 Epoch 37/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7896 - Precision: 0.7438 - Recall: 0.3485 - accuracy: 0.6173 - loss: 0.9829 Epoch 38/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7676 - Precision: 0.7082 - Recall: 0.3774 - accuracy: 0.5877 - loss: 0.9076 Epoch 39/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7474 - Precision: 0.7270 - Recall: 0.4120 - accuracy: 0.5567 - loss: 0.9420 Epoch 40/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7733 - Precision: 0.7286 - Recall: 0.4341 - accuracy: 0.5846 - loss: 0.8917 Epoch 41/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7767 - Precision: 0.7867 - Recall: 0.4049 - accuracy: 0.5782 - loss: 0.8606 Epoch 42/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7210 - Precision: 0.7715 - Recall: 0.3422 - accuracy: 0.5224 - loss: 0.9339 Epoch 43/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8248 - Precision: 0.8134 - Recall: 0.4608 - accuracy: 0.6238 - loss: 0.8029 Epoch 44/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7386 - Precision: 0.6928 - Recall: 0.3848 - accuracy: 0.5430 - loss: 0.9649 Epoch 45/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7964 - Precision: 0.7354 - Recall: 0.4606 - accuracy: 0.6375 - loss: 0.9191 Epoch 46/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7280 - Precision: 0.6100 - Recall: 0.3959 - accuracy: 0.5532 - loss: 0.9612 Epoch 47/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6970 - Precision: 0.5769 - Recall: 0.4284 - accuracy: 0.5389 - loss: 1.0102 Epoch 48/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7075 - Precision: 0.6350 - Recall: 0.4362 - accuracy: 0.5187 - loss: 0.9996 Epoch 49/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7345 - Precision: 0.7030 - Recall: 0.4512 - accuracy: 0.5726 - loss: 0.9138 Epoch 50/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7427 - Precision: 0.7587 - Recall: 0.3440 - accuracy: 0.5199 - loss: 0.9196 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 28ms/step Epoch 1/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 4s 4ms/step - AUC: 0.7183 - Precision: 0.5622 - Recall: 0.3940 - accuracy: 0.5211 - loss: 1.1014 Epoch 2/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7608 - Precision: 0.7914 - Recall: 0.3119 - accuracy: 0.5368 - loss: 0.8775 Epoch 3/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8216 - Precision: 0.7385 - Recall: 0.4388 - accuracy: 0.6160 - loss: 0.8016 Epoch 4/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8553 - Precision: 0.7800 - Recall: 0.4725 - accuracy: 0.6450 - loss: 0.7310 Epoch 5/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8572 - Precision: 0.7318 - Recall: 0.4864 - accuracy: 0.6462 - loss: 0.6976 Epoch 6/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8337 - Precision: 0.7983 - Recall: 0.4396 - accuracy: 0.6180 - loss: 0.7753 Epoch 7/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8386 - Precision: 0.7491 - Recall: 0.4253 - accuracy: 0.6451 - loss: 0.7789 Epoch 8/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8824 - Precision: 0.7882 - Recall: 0.5398 - accuracy: 0.6802 - loss: 0.6582 Epoch 9/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8617 - Precision: 0.7843 - Recall: 0.4882 - accuracy: 0.6380 - loss: 0.6849 Epoch 10/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8819 - Precision: 0.7817 - Recall: 0.5682 - accuracy: 0.7122 - loss: 0.6786 Epoch 11/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.8830 - Precision: 0.7788 - Recall: 0.5579 - accuracy: 0.7022 - loss: 0.6651 Epoch 12/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.8556 - Precision: 0.8025 - Recall: 0.5301 - accuracy: 0.6912 - loss: 0.7784 Epoch 13/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8966 - Precision: 0.8084 - Recall: 0.5866 - accuracy: 0.7181 - loss: 0.6317 Epoch 14/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8882 - Precision: 0.8215 - Recall: 0.5693 - accuracy: 0.7022 - loss: 0.6331 Epoch 15/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8681 - Precision: 0.7959 - Recall: 0.4623 - accuracy: 0.6756 - loss: 0.6956 Epoch 16/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8566 - Precision: 0.7869 - Recall: 0.5014 - accuracy: 0.6580 - loss: 0.7506 Epoch 17/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8597 - Precision: 0.7821 - Recall: 0.4670 - accuracy: 0.6722 - loss: 0.7392 Epoch 18/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8009 - Precision: 0.7052 - Recall: 0.3687 - accuracy: 0.6217 - loss: 0.9317 Epoch 19/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8740 - Precision: 0.8249 - Recall: 0.5162 - accuracy: 0.6884 - loss: 0.7054 Epoch 20/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8527 - Precision: 0.7590 - Recall: 0.5121 - accuracy: 0.6528 - loss: 0.7077 Epoch 21/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8849 - Precision: 0.7602 - Recall: 0.5773 - accuracy: 0.6866 - loss: 0.6438 Epoch 22/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8541 - Precision: 0.7266 - Recall: 0.4842 - accuracy: 0.6456 - loss: 0.7019 Epoch 23/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8584 - Precision: 0.7577 - Recall: 0.4771 - accuracy: 0.6394 - loss: 0.7282 Epoch 24/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8904 - Precision: 0.7969 - Recall: 0.5787 - accuracy: 0.7021 - loss: 0.6186 Epoch 25/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8776 - Precision: 0.7657 - Recall: 0.5105 - accuracy: 0.6630 - loss: 0.6628 Epoch 26/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.8781 - Precision: 0.7904 - Recall: 0.5191 - accuracy: 0.6769 - loss: 0.6430 Epoch 27/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8792 - Precision: 0.8284 - Recall: 0.5241 - accuracy: 0.6637 - loss: 0.6369 Epoch 28/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8893 - Precision: 0.7720 - Recall: 0.6044 - accuracy: 0.7056 - loss: 0.6355 Epoch 29/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8596 - Precision: 0.7731 - Recall: 0.4467 - accuracy: 0.6593 - loss: 0.7367 Epoch 30/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8772 - Precision: 0.8051 - Recall: 0.4784 - accuracy: 0.6992 - loss: 0.6575 Epoch 31/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8827 - Precision: 0.7692 - Recall: 0.5179 - accuracy: 0.6647 - loss: 0.6603 Epoch 32/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8536 - Precision: 0.7760 - Recall: 0.5140 - accuracy: 0.6247 - loss: 0.6807 Epoch 33/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8617 - Precision: 0.8130 - Recall: 0.4715 - accuracy: 0.6494 - loss: 0.6806 Epoch 34/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8763 - Precision: 0.8483 - Recall: 0.4904 - accuracy: 0.6651 - loss: 0.6730 Epoch 35/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8703 - Precision: 0.8173 - Recall: 0.4916 - accuracy: 0.6615 - loss: 0.6836 Epoch 36/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8847 - Precision: 0.8049 - Recall: 0.5411 - accuracy: 0.6975 - loss: 0.6716 Epoch 37/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8546 - Precision: 0.8072 - Recall: 0.4194 - accuracy: 0.6653 - loss: 0.7187 Epoch 38/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8613 - Precision: 0.7844 - Recall: 0.4929 - accuracy: 0.6413 - loss: 0.6773 Epoch 39/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8583 - Precision: 0.8058 - Recall: 0.4772 - accuracy: 0.6440 - loss: 0.7259 Epoch 40/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8760 - Precision: 0.7904 - Recall: 0.5290 - accuracy: 0.6819 - loss: 0.6803 Epoch 41/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8665 - Precision: 0.7932 - Recall: 0.5133 - accuracy: 0.6619 - loss: 0.6688 Epoch 42/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8580 - Precision: 0.7360 - Recall: 0.4930 - accuracy: 0.6178 - loss: 0.6786 Epoch 43/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8831 - Precision: 0.8103 - Recall: 0.5138 - accuracy: 0.6636 - loss: 0.6439 Epoch 44/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8890 - Precision: 0.7835 - Recall: 0.5880 - accuracy: 0.6944 - loss: 0.6540 Epoch 45/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8727 - Precision: 0.8424 - Recall: 0.5000 - accuracy: 0.6627 - loss: 0.6661 Epoch 46/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8551 - Precision: 0.7892 - Recall: 0.4964 - accuracy: 0.6519 - loss: 0.7452 Epoch 47/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8601 - Precision: 0.8029 - Recall: 0.5195 - accuracy: 0.6521 - loss: 0.7035 Epoch 48/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8693 - Precision: 0.7636 - Recall: 0.5103 - accuracy: 0.6580 - loss: 0.6757 Epoch 49/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8900 - Precision: 0.7905 - Recall: 0.5467 - accuracy: 0.6878 - loss: 0.6023 Epoch 50/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8405 - Precision: 0.7851 - Recall: 0.3999 - accuracy: 0.6274 - loss: 0.7284 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 28ms/step Epoch 1/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 4s 4ms/step - AUC: 0.6145 - Precision: 0.5017 - Recall: 0.2747 - accuracy: 0.4302 - loss: 1.1356 Epoch 2/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8271 - Precision: 0.7650 - Recall: 0.4831 - accuracy: 0.6342 - loss: 0.8030 Epoch 3/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8189 - Precision: 0.7072 - Recall: 0.4821 - accuracy: 0.6221 - loss: 0.8247 Epoch 4/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8470 - Precision: 0.7796 - Recall: 0.4443 - accuracy: 0.6470 - loss: 0.7259 Epoch 5/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8453 - Precision: 0.7536 - Recall: 0.4875 - accuracy: 0.6282 - loss: 0.7098 Epoch 6/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8731 - Precision: 0.7486 - Recall: 0.5321 - accuracy: 0.6646 - loss: 0.6696 Epoch 7/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8748 - Precision: 0.8215 - Recall: 0.4685 - accuracy: 0.6618 - loss: 0.6639 Epoch 8/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8765 - Precision: 0.7674 - Recall: 0.4973 - accuracy: 0.6759 - loss: 0.6487 Epoch 9/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8773 - Precision: 0.7936 - Recall: 0.5148 - accuracy: 0.6571 - loss: 0.6332 Epoch 10/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8842 - Precision: 0.7902 - Recall: 0.5563 - accuracy: 0.6923 - loss: 0.6368 Epoch 11/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8849 - Precision: 0.8002 - Recall: 0.5435 - accuracy: 0.6897 - loss: 0.6280 Epoch 12/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8849 - Precision: 0.7759 - Recall: 0.5003 - accuracy: 0.7027 - loss: 0.6406 Epoch 13/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8722 - Precision: 0.7413 - Recall: 0.4959 - accuracy: 0.6323 - loss: 0.6353 Epoch 14/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8563 - Precision: 0.7618 - Recall: 0.4557 - accuracy: 0.6173 - loss: 0.6836 Epoch 15/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8828 - Precision: 0.7501 - Recall: 0.5383 - accuracy: 0.6769 - loss: 0.6197 Epoch 16/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8826 - Precision: 0.7630 - Recall: 0.5416 - accuracy: 0.6632 - loss: 0.6128 Epoch 17/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.8975 - Precision: 0.8175 - Recall: 0.5369 - accuracy: 0.6714 - loss: 0.5799 Epoch 18/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8750 - Precision: 0.7309 - Recall: 0.4909 - accuracy: 0.6492 - loss: 0.6143 Epoch 19/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9140 - Precision: 0.8131 - Recall: 0.6243 - accuracy: 0.7287 - loss: 0.5298 Epoch 20/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8946 - Precision: 0.7568 - Recall: 0.6032 - accuracy: 0.6995 - loss: 0.5868 Epoch 21/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.8927 - Precision: 0.8353 - Recall: 0.5275 - accuracy: 0.6924 - loss: 0.6043 Epoch 22/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8922 - Precision: 0.7543 - Recall: 0.5992 - accuracy: 0.6874 - loss: 0.5925 Epoch 23/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9040 - Precision: 0.8146 - Recall: 0.5952 - accuracy: 0.7437 - loss: 0.5837 Epoch 24/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8852 - Precision: 0.7150 - Recall: 0.5774 - accuracy: 0.6636 - loss: 0.6157 Epoch 25/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8909 - Precision: 0.7509 - Recall: 0.5385 - accuracy: 0.6602 - loss: 0.5918 Epoch 26/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8850 - Precision: 0.7738 - Recall: 0.5275 - accuracy: 0.6789 - loss: 0.6319 Epoch 27/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8910 - Precision: 0.8304 - Recall: 0.4950 - accuracy: 0.6662 - loss: 0.5859 Epoch 28/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9058 - Precision: 0.7599 - Recall: 0.6391 - accuracy: 0.7080 - loss: 0.5543 Epoch 29/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9106 - Precision: 0.8081 - Recall: 0.5788 - accuracy: 0.7403 - loss: 0.5490 Epoch 30/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8916 - Precision: 0.7714 - Recall: 0.5296 - accuracy: 0.6916 - loss: 0.5825 Epoch 31/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9088 - Precision: 0.7664 - Recall: 0.5802 - accuracy: 0.6812 - loss: 0.5068 Epoch 32/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9078 - Precision: 0.7708 - Recall: 0.6387 - accuracy: 0.7185 - loss: 0.5336 Epoch 33/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8851 - Precision: 0.7964 - Recall: 0.4753 - accuracy: 0.6821 - loss: 0.6078 Epoch 34/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9058 - Precision: 0.8233 - Recall: 0.5720 - accuracy: 0.7236 - loss: 0.5610 Epoch 35/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9132 - Precision: 0.7833 - Recall: 0.6478 - accuracy: 0.7339 - loss: 0.5403 Epoch 36/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8996 - Precision: 0.7728 - Recall: 0.5695 - accuracy: 0.7066 - loss: 0.5625 Epoch 37/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8830 - Precision: 0.7730 - Recall: 0.5142 - accuracy: 0.6471 - loss: 0.5960 Epoch 38/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.8712 - Precision: 0.7588 - Recall: 0.5024 - accuracy: 0.6468 - loss: 0.6988 Epoch 39/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9042 - Precision: 0.7681 - Recall: 0.6159 - accuracy: 0.7108 - loss: 0.5487 Epoch 40/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8912 - Precision: 0.8328 - Recall: 0.4874 - accuracy: 0.6579 - loss: 0.5943 Epoch 41/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8803 - Precision: 0.7326 - Recall: 0.5245 - accuracy: 0.6753 - loss: 0.6219 Epoch 42/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9018 - Precision: 0.7895 - Recall: 0.5862 - accuracy: 0.7133 - loss: 0.5753 Epoch 43/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8904 - Precision: 0.7167 - Recall: 0.5695 - accuracy: 0.6712 - loss: 0.5745 Epoch 44/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9025 - Precision: 0.7869 - Recall: 0.5772 - accuracy: 0.6995 - loss: 0.5425 Epoch 45/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9030 - Precision: 0.7597 - Recall: 0.6005 - accuracy: 0.7019 - loss: 0.5535 Epoch 46/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9024 - Precision: 0.7931 - Recall: 0.5897 - accuracy: 0.7047 - loss: 0.5713 Epoch 47/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8922 - Precision: 0.7569 - Recall: 0.5881 - accuracy: 0.6822 - loss: 0.5754 Epoch 48/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9049 - Precision: 0.8341 - Recall: 0.5015 - accuracy: 0.6981 - loss: 0.5389 Epoch 49/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8946 - Precision: 0.7490 - Recall: 0.5998 - accuracy: 0.6800 - loss: 0.5674 Epoch 50/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9115 - Precision: 0.7869 - Recall: 0.5863 - accuracy: 0.7212 - loss: 0.5495 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 27ms/step Epoch 1/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 5s 5ms/step - AUC: 0.6209 - Precision: 0.4823 - Recall: 0.3220 - accuracy: 0.4820 - loss: 1.3226 Epoch 2/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6900 - Precision: 0.6368 - Recall: 0.2966 - accuracy: 0.4955 - loss: 1.0366 Epoch 3/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6488 - Precision: 0.7328 - Recall: 0.2271 - accuracy: 0.4624 - loss: 1.0013 Epoch 4/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6805 - Precision: 0.7109 - Recall: 0.1997 - accuracy: 0.4873 - loss: 1.0544 Epoch 5/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7043 - Precision: 0.7989 - Recall: 0.2783 - accuracy: 0.4956 - loss: 0.9640 Epoch 6/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7462 - Precision: 0.7591 - Recall: 0.3076 - accuracy: 0.5442 - loss: 0.9284 Epoch 7/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7064 - Precision: 0.7219 - Recall: 0.2629 - accuracy: 0.5014 - loss: 1.0529 Epoch 8/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7315 - Precision: 0.8192 - Recall: 0.2936 - accuracy: 0.5628 - loss: 0.9448 Epoch 9/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7383 - Precision: 0.8322 - Recall: 0.2743 - accuracy: 0.5598 - loss: 0.9084 Epoch 10/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6690 - Precision: 0.7527 - Recall: 0.1780 - accuracy: 0.4702 - loss: 1.0044 Epoch 11/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6863 - Precision: 0.7274 - Recall: 0.2379 - accuracy: 0.4926 - loss: 0.9867 Epoch 12/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7387 - Precision: 0.8367 - Recall: 0.2854 - accuracy: 0.5361 - loss: 0.9004 Epoch 13/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7239 - Precision: 0.8443 - Recall: 0.2689 - accuracy: 0.5087 - loss: 1.0119 Epoch 14/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7272 - Precision: 0.8353 - Recall: 0.2583 - accuracy: 0.5434 - loss: 1.0155 Epoch 15/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6834 - Precision: 0.7992 - Recall: 0.2453 - accuracy: 0.4608 - loss: 0.9974 Epoch 16/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6849 - Precision: 0.8383 - Recall: 0.2096 - accuracy: 0.4682 - loss: 0.9755 Epoch 17/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7329 - Precision: 0.8243 - Recall: 0.2777 - accuracy: 0.5303 - loss: 0.9114 Epoch 18/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6219 - Precision: 0.7362 - Recall: 0.1770 - accuracy: 0.4168 - loss: 1.0862 Epoch 19/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6514 - Precision: 0.7094 - Recall: 0.1921 - accuracy: 0.4348 - loss: 1.0854 Epoch 20/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6803 - Precision: 0.7788 - Recall: 0.1962 - accuracy: 0.4857 - loss: 1.1309 Epoch 21/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6946 - Precision: 0.8568 - Recall: 0.2332 - accuracy: 0.4823 - loss: 0.9442 Epoch 22/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7057 - Precision: 0.8625 - Recall: 0.2105 - accuracy: 0.5020 - loss: 0.9630 Epoch 23/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6919 - Precision: 0.8654 - Recall: 0.2284 - accuracy: 0.4572 - loss: 0.9404 Epoch 24/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6897 - Precision: 0.8304 - Recall: 0.2437 - accuracy: 0.4700 - loss: 0.9838 Epoch 25/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6709 - Precision: 0.8097 - Recall: 0.1810 - accuracy: 0.4821 - loss: 1.1119 Epoch 26/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7183 - Precision: 0.8288 - Recall: 0.2687 - accuracy: 0.5151 - loss: 0.9975 Epoch 27/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7017 - Precision: 0.7920 - Recall: 0.2362 - accuracy: 0.4989 - loss: 0.9550 Epoch 28/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7152 - Precision: 0.9014 - Recall: 0.2570 - accuracy: 0.4813 - loss: 0.9142 Epoch 29/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6574 - Precision: 0.8579 - Recall: 0.2114 - accuracy: 0.4488 - loss: 0.9891 Epoch 30/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7127 - Precision: 0.8654 - Recall: 0.2548 - accuracy: 0.5377 - loss: 0.9464 Epoch 31/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7157 - Precision: 0.8464 - Recall: 0.2268 - accuracy: 0.5453 - loss: 0.9876 Epoch 32/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7319 - Precision: 0.8589 - Recall: 0.2558 - accuracy: 0.5271 - loss: 0.9643 Epoch 33/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7589 - Precision: 0.9050 - Recall: 0.2560 - accuracy: 0.5714 - loss: 0.8730 Epoch 34/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7412 - Precision: 0.8937 - Recall: 0.2577 - accuracy: 0.5184 - loss: 0.9094 Epoch 35/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7373 - Precision: 0.8701 - Recall: 0.2410 - accuracy: 0.5514 - loss: 0.9237 Epoch 36/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7202 - Precision: 0.8398 - Recall: 0.2188 - accuracy: 0.5078 - loss: 0.9585 Epoch 37/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7270 - Precision: 0.8715 - Recall: 0.2440 - accuracy: 0.5182 - loss: 0.9274 Epoch 38/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7501 - Precision: 0.8927 - Recall: 0.2765 - accuracy: 0.5436 - loss: 0.8877 Epoch 39/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7247 - Precision: 0.8639 - Recall: 0.2523 - accuracy: 0.5121 - loss: 0.9603 Epoch 40/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7453 - Precision: 0.8938 - Recall: 0.2572 - accuracy: 0.5321 - loss: 0.8911 Epoch 41/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7422 - Precision: 0.8966 - Recall: 0.2396 - accuracy: 0.5269 - loss: 0.9127 Epoch 42/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7280 - Precision: 0.9009 - Recall: 0.2673 - accuracy: 0.5277 - loss: 0.9074 Epoch 43/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6990 - Precision: 0.8224 - Recall: 0.2313 - accuracy: 0.4868 - loss: 0.9818 Epoch 44/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7350 - Precision: 0.8851 - Recall: 0.2654 - accuracy: 0.5193 - loss: 0.9207 Epoch 45/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7745 - Precision: 0.9017 - Recall: 0.2869 - accuracy: 0.5751 - loss: 0.8702 Epoch 46/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7150 - Precision: 0.8901 - Recall: 0.2495 - accuracy: 0.5010 - loss: 0.9106 Epoch 47/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.7343 - Precision: 0.9046 - Recall: 0.2634 - accuracy: 0.5332 - loss: 0.8928 Epoch 48/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6651 - Precision: 0.8566 - Recall: 0.2128 - accuracy: 0.4902 - loss: 1.1157 Epoch 49/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7343 - Precision: 0.9151 - Recall: 0.2549 - accuracy: 0.5170 - loss: 0.8905 Epoch 50/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6846 - Precision: 0.8857 - Recall: 0.2244 - accuracy: 0.4832 - loss: 1.0451 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step Epoch 1/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 5s 6ms/step - AUC: 0.5336 - Precision: 0.3803 - Recall: 0.2361 - accuracy: 0.3390 - loss: 1.6265 Epoch 2/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6604 - Precision: 0.6547 - Recall: 0.2452 - accuracy: 0.4547 - loss: 1.0255 Epoch 3/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7115 - Precision: 0.7401 - Recall: 0.2730 - accuracy: 0.5224 - loss: 0.9532 Epoch 4/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7864 - Precision: 0.8475 - Recall: 0.3471 - accuracy: 0.5676 - loss: 0.8592 Epoch 5/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7928 - Precision: 0.8351 - Recall: 0.3326 - accuracy: 0.5711 - loss: 0.8335 Epoch 6/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7662 - Precision: 0.8780 - Recall: 0.3147 - accuracy: 0.5510 - loss: 0.8759 Epoch 7/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7479 - Precision: 0.8305 - Recall: 0.3062 - accuracy: 0.5255 - loss: 0.8894 Epoch 8/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7550 - Precision: 0.8712 - Recall: 0.2864 - accuracy: 0.5590 - loss: 0.8611 Epoch 9/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7933 - Precision: 0.8630 - Recall: 0.3361 - accuracy: 0.5723 - loss: 0.8321 Epoch 10/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8082 - Precision: 0.8688 - Recall: 0.3597 - accuracy: 0.6033 - loss: 0.8068 Epoch 11/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8170 - Precision: 0.8637 - Recall: 0.3560 - accuracy: 0.5887 - loss: 0.8003 Epoch 12/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8026 - Precision: 0.9087 - Recall: 0.3519 - accuracy: 0.5966 - loss: 0.8333 Epoch 13/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8163 - Precision: 0.8762 - Recall: 0.3798 - accuracy: 0.5881 - loss: 0.7747 Epoch 14/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8360 - Precision: 0.8539 - Recall: 0.3819 - accuracy: 0.6340 - loss: 0.7837 Epoch 15/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7832 - Precision: 0.8465 - Recall: 0.3295 - accuracy: 0.5721 - loss: 0.8861 Epoch 16/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8151 - Precision: 0.8406 - Recall: 0.3516 - accuracy: 0.6060 - loss: 0.8047 Epoch 17/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7886 - Precision: 0.8936 - Recall: 0.3233 - accuracy: 0.5736 - loss: 0.8685 Epoch 18/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8306 - Precision: 0.8725 - Recall: 0.3895 - accuracy: 0.6298 - loss: 0.7976 Epoch 19/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8276 - Precision: 0.8597 - Recall: 0.3643 - accuracy: 0.6213 - loss: 0.8250 Epoch 20/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8130 - Precision: 0.8694 - Recall: 0.3696 - accuracy: 0.5946 - loss: 0.8337 Epoch 21/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8560 - Precision: 0.8697 - Recall: 0.4306 - accuracy: 0.6477 - loss: 0.7335 Epoch 22/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7785 - Precision: 0.8440 - Recall: 0.2935 - accuracy: 0.5582 - loss: 0.9234 Epoch 23/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8112 - Precision: 0.8428 - Recall: 0.3534 - accuracy: 0.6222 - loss: 0.8467 Epoch 24/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7841 - Precision: 0.8943 - Recall: 0.3262 - accuracy: 0.5635 - loss: 0.8432 Epoch 25/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8103 - Precision: 0.8980 - Recall: 0.3270 - accuracy: 0.6209 - loss: 0.8993 Epoch 26/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7623 - Precision: 0.8773 - Recall: 0.2626 - accuracy: 0.5548 - loss: 0.8833 Epoch 27/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8143 - Precision: 0.9239 - Recall: 0.3315 - accuracy: 0.5949 - loss: 0.7743 Epoch 28/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8492 - Precision: 0.8896 - Recall: 0.3927 - accuracy: 0.6571 - loss: 0.7106 Epoch 29/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8297 - Precision: 0.8660 - Recall: 0.3750 - accuracy: 0.6312 - loss: 0.7526 Epoch 30/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8004 - Precision: 0.9126 - Recall: 0.3264 - accuracy: 0.5702 - loss: 0.8419 Epoch 31/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7935 - Precision: 0.8697 - Recall: 0.3286 - accuracy: 0.6041 - loss: 0.8622 Epoch 32/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8328 - Precision: 0.8703 - Recall: 0.3768 - accuracy: 0.6211 - loss: 0.7879 Epoch 33/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8284 - Precision: 0.8682 - Recall: 0.3997 - accuracy: 0.6139 - loss: 0.7405 Epoch 34/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8116 - Precision: 0.8851 - Recall: 0.3435 - accuracy: 0.6171 - loss: 0.8650 Epoch 35/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8270 - Precision: 0.9136 - Recall: 0.3808 - accuracy: 0.6033 - loss: 0.7562 Epoch 36/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8543 - Precision: 0.8826 - Recall: 0.4008 - accuracy: 0.6407 - loss: 0.7519 Epoch 37/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8204 - Precision: 0.9073 - Recall: 0.3541 - accuracy: 0.6038 - loss: 0.7831 Epoch 38/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8400 - Precision: 0.8779 - Recall: 0.4048 - accuracy: 0.6266 - loss: 0.7237 Epoch 39/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8032 - Precision: 0.9158 - Recall: 0.3427 - accuracy: 0.6169 - loss: 0.8007 Epoch 40/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8182 - Precision: 0.9249 - Recall: 0.3604 - accuracy: 0.6243 - loss: 0.7659 Epoch 41/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8297 - Precision: 0.9301 - Recall: 0.3423 - accuracy: 0.6124 - loss: 0.7370 Epoch 42/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8204 - Precision: 0.8786 - Recall: 0.3431 - accuracy: 0.5872 - loss: 0.8412 Epoch 43/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8249 - Precision: 0.8954 - Recall: 0.3745 - accuracy: 0.6129 - loss: 0.7966 Epoch 44/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8456 - Precision: 0.9047 - Recall: 0.3818 - accuracy: 0.6429 - loss: 0.6982 Epoch 45/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8401 - Precision: 0.8805 - Recall: 0.3889 - accuracy: 0.6292 - loss: 0.7117 Epoch 46/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8208 - Precision: 0.8714 - Recall: 0.3636 - accuracy: 0.5947 - loss: 0.8358 Epoch 47/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8292 - Precision: 0.9549 - Recall: 0.3751 - accuracy: 0.6056 - loss: 0.7547 Epoch 48/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7952 - Precision: 0.8634 - Recall: 0.3181 - accuracy: 0.5869 - loss: 0.9262 Epoch 49/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8175 - Precision: 0.8983 - Recall: 0.3496 - accuracy: 0.6313 - loss: 0.8050 Epoch 50/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8271 - Precision: 0.9142 - Recall: 0.3878 - accuracy: 0.6146 - loss: 0.7389 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 28ms/step Epoch 1/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 4s 7ms/step - AUC: 0.5842 - Precision: 0.4309 - Recall: 0.3231 - accuracy: 0.4325 - loss: 1.4550 Epoch 2/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.7224 - Precision: 0.6708 - Recall: 0.3226 - accuracy: 0.5167 - loss: 1.0051 Epoch 3/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7519 - Precision: 0.7415 - Recall: 0.3503 - accuracy: 0.5175 - loss: 0.9102 Epoch 4/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8034 - Precision: 0.8061 - Recall: 0.3955 - accuracy: 0.5723 - loss: 0.7954 Epoch 5/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8145 - Precision: 0.8223 - Recall: 0.3739 - accuracy: 0.5799 - loss: 0.7893 Epoch 6/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8245 - Precision: 0.7768 - Recall: 0.4175 - accuracy: 0.5996 - loss: 0.7801 Epoch 7/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8332 - Precision: 0.7858 - Recall: 0.4285 - accuracy: 0.6371 - loss: 0.7537 Epoch 8/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8417 - Precision: 0.7660 - Recall: 0.4697 - accuracy: 0.6628 - loss: 0.7478 Epoch 9/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8387 - Precision: 0.8497 - Recall: 0.4275 - accuracy: 0.6524 - loss: 0.7421 Epoch 10/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8285 - Precision: 0.7502 - Recall: 0.4932 - accuracy: 0.6071 - loss: 0.7599 Epoch 11/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8602 - Precision: 0.8329 - Recall: 0.4288 - accuracy: 0.6482 - loss: 0.7161 Epoch 12/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8219 - Precision: 0.7175 - Recall: 0.4626 - accuracy: 0.6072 - loss: 0.8046 Epoch 13/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8600 - Precision: 0.7807 - Recall: 0.5348 - accuracy: 0.6932 - loss: 0.7245 Epoch 14/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8557 - Precision: 0.8917 - Recall: 0.4337 - accuracy: 0.6467 - loss: 0.7189 Epoch 15/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8614 - Precision: 0.8448 - Recall: 0.4709 - accuracy: 0.6686 - loss: 0.6958 Epoch 16/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8528 - Precision: 0.7557 - Recall: 0.4245 - accuracy: 0.6541 - loss: 0.7102 Epoch 17/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8729 - Precision: 0.8289 - Recall: 0.4509 - accuracy: 0.6595 - loss: 0.6847 Epoch 18/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.8553 - Precision: 0.7974 - Recall: 0.4455 - accuracy: 0.6399 - loss: 0.7217 Epoch 19/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8582 - Precision: 0.8331 - Recall: 0.4581 - accuracy: 0.6849 - loss: 0.7180 Epoch 20/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8577 - Precision: 0.8410 - Recall: 0.4310 - accuracy: 0.6443 - loss: 0.6985 Epoch 21/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8747 - Precision: 0.8001 - Recall: 0.5052 - accuracy: 0.6651 - loss: 0.6686 Epoch 22/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8574 - Precision: 0.7885 - Recall: 0.4514 - accuracy: 0.6325 - loss: 0.6952 Epoch 23/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8715 - Precision: 0.8974 - Recall: 0.4182 - accuracy: 0.6640 - loss: 0.6688 Epoch 24/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8578 - Precision: 0.7943 - Recall: 0.4574 - accuracy: 0.6393 - loss: 0.6792 Epoch 25/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8799 - Precision: 0.8763 - Recall: 0.4791 - accuracy: 0.6963 - loss: 0.6544 Epoch 26/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8685 - Precision: 0.8381 - Recall: 0.4518 - accuracy: 0.6661 - loss: 0.7055 Epoch 27/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8748 - Precision: 0.8218 - Recall: 0.4584 - accuracy: 0.6782 - loss: 0.6968 Epoch 28/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8406 - Precision: 0.8076 - Recall: 0.3976 - accuracy: 0.6087 - loss: 0.7044 Epoch 29/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8596 - Precision: 0.7949 - Recall: 0.4601 - accuracy: 0.6430 - loss: 0.6843 Epoch 30/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.8610 - Precision: 0.8391 - Recall: 0.4437 - accuracy: 0.6152 - loss: 0.6777 Epoch 31/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8521 - Precision: 0.8122 - Recall: 0.4594 - accuracy: 0.6607 - loss: 0.7468 Epoch 32/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8536 - Precision: 0.7814 - Recall: 0.4493 - accuracy: 0.6459 - loss: 0.6949 Epoch 33/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8617 - Precision: 0.8684 - Recall: 0.4353 - accuracy: 0.6333 - loss: 0.6928 Epoch 34/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8624 - Precision: 0.8118 - Recall: 0.4360 - accuracy: 0.6122 - loss: 0.6826 Epoch 35/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.8414 - Precision: 0.8163 - Recall: 0.3991 - accuracy: 0.6153 - loss: 0.7350 Epoch 36/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8809 - Precision: 0.7946 - Recall: 0.5031 - accuracy: 0.6695 - loss: 0.6310 Epoch 37/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8591 - Precision: 0.8364 - Recall: 0.4420 - accuracy: 0.6638 - loss: 0.6937 Epoch 38/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8655 - Precision: 0.8668 - Recall: 0.4471 - accuracy: 0.6591 - loss: 0.6708 Epoch 39/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8540 - Precision: 0.8146 - Recall: 0.4290 - accuracy: 0.5985 - loss: 0.6796 Epoch 40/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8716 - Precision: 0.8405 - Recall: 0.4189 - accuracy: 0.6852 - loss: 0.6511 Epoch 41/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8520 - Precision: 0.8189 - Recall: 0.3930 - accuracy: 0.6618 - loss: 0.7798 Epoch 42/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8443 - Precision: 0.8588 - Recall: 0.4150 - accuracy: 0.6414 - loss: 0.7539 Epoch 43/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8578 - Precision: 0.8012 - Recall: 0.4468 - accuracy: 0.6570 - loss: 0.6867 Epoch 44/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8092 - Precision: 0.8516 - Recall: 0.3459 - accuracy: 0.5968 - loss: 0.9417 Epoch 45/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8496 - Precision: 0.8341 - Recall: 0.4683 - accuracy: 0.6295 - loss: 0.6967 Epoch 46/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8530 - Precision: 0.8319 - Recall: 0.4065 - accuracy: 0.6643 - loss: 0.7264 Epoch 47/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8611 - Precision: 0.8800 - Recall: 0.4169 - accuracy: 0.6759 - loss: 0.8219 Epoch 48/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8565 - Precision: 0.7642 - Recall: 0.4709 - accuracy: 0.6269 - loss: 0.6707 Epoch 49/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8427 - Precision: 0.8783 - Recall: 0.4044 - accuracy: 0.6278 - loss: 0.7333 Epoch 50/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8492 - Precision: 0.8127 - Recall: 0.4219 - accuracy: 0.6062 - loss: 0.6853 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 35ms/step Epoch 1/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 4s 5ms/step - AUC: 0.5839 - Precision: 0.4212 - Recall: 0.3179 - accuracy: 0.3858 - loss: 2.0556 Epoch 2/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5652 - Precision: 0.4085 - Recall: 0.1862 - accuracy: 0.4275 - loss: 1.3570 Epoch 3/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5937 - Precision: 0.4120 - Recall: 0.1332 - accuracy: 0.4491 - loss: 1.1071 Epoch 4/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5772 - Precision: 0.4289 - Recall: 0.1111 - accuracy: 0.4299 - loss: 1.1137 Epoch 5/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6505 - Precision: 0.5733 - Recall: 0.2137 - accuracy: 0.5294 - loss: 1.0657 Epoch 6/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6383 - Precision: 0.5439 - Recall: 0.1937 - accuracy: 0.5240 - loss: 1.0684 Epoch 7/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6021 - Precision: 0.5074 - Recall: 0.1007 - accuracy: 0.4629 - loss: 1.1204 Epoch 8/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5995 - Precision: 0.4716 - Recall: 0.1127 - accuracy: 0.4616 - loss: 1.0737 Epoch 9/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6140 - Precision: 0.4423 - Recall: 0.0683 - accuracy: 0.4857 - loss: 1.0752 Epoch 10/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6156 - Precision: 0.4833 - Recall: 0.3451 - accuracy: 0.4689 - loss: 1.0810 Epoch 11/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5995 - Precision: 0.4381 - Recall: 0.3241 - accuracy: 0.4944 - loss: 1.0604 Epoch 12/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6249 - Precision: 0.4790 - Recall: 0.0653 - accuracy: 0.5014 - loss: 1.0569 Epoch 13/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6169 - Precision: 0.4984 - Recall: 0.0948 - accuracy: 0.4862 - loss: 1.0557 Epoch 14/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5915 - Precision: 0.3865 - Recall: 0.1101 - accuracy: 0.4593 - loss: 1.0943 Epoch 15/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6446 - Precision: 0.5374 - Recall: 0.5068 - accuracy: 0.5325 - loss: 1.0238 Epoch 16/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5993 - Precision: 0.2670 - Recall: 0.0067 - accuracy: 0.4827 - loss: 1.0632 Epoch 17/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6298 - Precision: 0.4821 - Recall: 0.3703 - accuracy: 0.5228 - loss: 1.0280 Epoch 18/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6258 - Precision: 0.4948 - Recall: 0.0347 - accuracy: 0.5169 - loss: 1.0322 Epoch 19/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6343 - Precision: 0.5031 - Recall: 0.1166 - accuracy: 0.5171 - loss: 1.0452 Epoch 20/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6249 - Precision: 0.4008 - Recall: 0.0259 - accuracy: 0.5079 - loss: 1.0363 Epoch 21/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6072 - Precision: 0.0820 - Recall: 0.0070 - accuracy: 0.4917 - loss: 1.0489 1 Epoch 22/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6317 - Precision: 0.4494 - Recall: 0.2947 - accuracy: 0.5073 - loss: 1.0346 Epoch 23/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5954 - Precision: 0.1890 - Recall: 0.0271 - accuracy: 0.4916 - loss: 1.0480 Epoch 24/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.5990 - Precision: 0.2703 - Recall: 0.0561 - accuracy: 0.4657 - loss: 1.0698 Epoch 25/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6125 - Precision: 0.4066 - Recall: 0.1348 - accuracy: 0.4861 - loss: 1.0841 Epoch 26/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6027 - Precision: 0.4739 - Recall: 0.2620 - accuracy: 0.4892 - loss: 1.0537 Epoch 27/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5957 - Precision: 0.1830 - Recall: 0.0245 - accuracy: 0.4901 - loss: 1.0483 Epoch 28/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5911 - Precision: 0.0770 - Recall: 0.0019 - accuracy: 0.4819 - loss: 1.0520 Epoch 29/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6152 - Precision: 0.3472 - Recall: 0.1140 - accuracy: 0.4888 - loss: 1.0499 Epoch 30/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6122 - Precision: 0.1342 - Recall: 0.0054 - accuracy: 0.4935 - loss: 1.0451 Epoch 31/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6450 - Precision: 0.5505 - Recall: 0.5364 - accuracy: 0.5487 - loss: 1.0056 Epoch 32/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5931 - Precision: 0.0127 - Recall: 2.0303e-04 - accuracy: 0.4698 - loss: 1.0606 Epoch 33/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6511 - Precision: 0.5491 - Recall: 0.5199 - accuracy: 0.5505 - loss: 1.0044 Epoch 34/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6288 - Precision: 0.3210 - Recall: 0.1236 - accuracy: 0.5153 - loss: 1.0331 Epoch 35/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6151 - Precision: 0.2711 - Recall: 0.0749 - accuracy: 0.4808 - loss: 1.0518 Epoch 36/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6248 - Precision: 0.4252 - Recall: 0.0654 - accuracy: 0.4884 - loss: 1.0515 Epoch 37/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5966 - Precision: 0.3400 - Recall: 0.0952 - accuracy: 0.4979 - loss: 1.0428 Epoch 38/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6147 - Precision: 0.5334 - Recall: 0.0303 - accuracy: 0.4808 - loss: 1.0944 Epoch 39/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6201 - Precision: 0.5155 - Recall: 0.4812 - accuracy: 0.5162 - loss: 1.0907 Epoch 40/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6291 - Precision: 0.3831 - Recall: 0.1226 - accuracy: 0.5094 - loss: 1.0337 Epoch 41/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6002 - Precision: 0.0469 - Recall: 0.0022 - accuracy: 0.4817 - loss: 1.0933 Epoch 42/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6107 - Precision: 0.5014 - Recall: 0.3669 - accuracy: 0.4966 - loss: 1.0453 Epoch 43/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6034 - Precision: 0.4588 - Recall: 0.2723 - accuracy: 0.4855 - loss: 1.0556 Epoch 44/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6239 - Precision: 0.5053 - Recall: 0.4736 - accuracy: 0.5032 - loss: 1.0372 Epoch 45/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6252 - Precision: 0.4129 - Recall: 0.1637 - accuracy: 0.5056 - loss: 1.0377 Epoch 46/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6027 - Precision: 0.4061 - Recall: 0.1370 - accuracy: 0.4811 - loss: 1.0542 Epoch 47/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5967 - Precision: 0.3334 - Recall: 0.0504 - accuracy: 0.4673 - loss: 1.0629 Epoch 48/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6017 - Precision: 0.4612 - Recall: 0.2141 - accuracy: 0.4744 - loss: 1.0581 Epoch 49/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6156 - Precision: 0.4869 - Recall: 0.3781 - accuracy: 0.5026 - loss: 1.0402 Epoch 50/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6101 - Precision: 0.4103 - Recall: 0.1920 - accuracy: 0.4898 - loss: 1.0466 5/5 ━━━━━━━━━━━━━━━━━━━━ 1s 70ms/step Epoch 1/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 4s 5ms/step - AUC: 0.5450 - Precision: 0.3745 - Recall: 0.3094 - accuracy: 0.3538 - loss: 2.7938 Epoch 2/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5724 - Precision: 0.4117 - Recall: 0.2481 - accuracy: 0.4175 - loss: 1.5314 Epoch 3/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5620 - Precision: 0.4389 - Recall: 0.1760 - accuracy: 0.4415 - loss: 1.3026 Epoch 4/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5936 - Precision: 0.4621 - Recall: 0.1440 - accuracy: 0.4497 - loss: 1.1380 Epoch 5/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5886 - Precision: 0.4857 - Recall: 0.1343 - accuracy: 0.4407 - loss: 1.1292 Epoch 6/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6223 - Precision: 0.4759 - Recall: 0.1338 - accuracy: 0.5115 - loss: 1.0700 Epoch 7/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6102 - Precision: 0.5291 - Recall: 0.1046 - accuracy: 0.4717 - loss: 1.0843 Epoch 8/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6218 - Precision: 0.5341 - Recall: 0.1196 - accuracy: 0.4621 - loss: 1.0571 Epoch 9/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6329 - Precision: 0.5479 - Recall: 0.1559 - accuracy: 0.5001 - loss: 1.0565 Epoch 10/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5932 - Precision: 0.4921 - Recall: 0.0985 - accuracy: 0.4605 - loss: 1.0685 Epoch 11/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6324 - Precision: 0.5656 - Recall: 0.1559 - accuracy: 0.4975 - loss: 1.0574 Epoch 12/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6511 - Precision: 0.6367 - Recall: 0.1434 - accuracy: 0.4957 - loss: 1.0378 Epoch 13/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6280 - Precision: 0.6363 - Recall: 0.1686 - accuracy: 0.4493 - loss: 1.0662 Epoch 14/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6853 - Precision: 0.7667 - Recall: 0.1975 - accuracy: 0.5149 - loss: 1.0024 Epoch 15/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6522 - Precision: 0.6513 - Recall: 0.1729 - accuracy: 0.4788 - loss: 1.0093 Epoch 16/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6679 - Precision: 0.6908 - Recall: 0.1913 - accuracy: 0.5128 - loss: 1.0634 Epoch 17/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6894 - Precision: 0.7023 - Recall: 0.1829 - accuracy: 0.5140 - loss: 1.0277 Epoch 18/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6729 - Precision: 0.7142 - Recall: 0.2068 - accuracy: 0.4835 - loss: 0.9968 Epoch 19/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7070 - Precision: 0.8403 - Recall: 0.2459 - accuracy: 0.5115 - loss: 0.9118 Epoch 20/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6907 - Precision: 0.8299 - Recall: 0.2020 - accuracy: 0.4911 - loss: 0.9731 Epoch 21/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6511 - Precision: 0.7087 - Recall: 0.1857 - accuracy: 0.4749 - loss: 1.0320 Epoch 22/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7051 - Precision: 0.7678 - Recall: 0.2149 - accuracy: 0.5190 - loss: 0.9738 Epoch 23/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7012 - Precision: 0.7969 - Recall: 0.1949 - accuracy: 0.5247 - loss: 0.9959 Epoch 24/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6545 - Precision: 0.7660 - Recall: 0.1851 - accuracy: 0.4778 - loss: 1.0509 Epoch 25/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7104 - Precision: 0.8555 - Recall: 0.2096 - accuracy: 0.5151 - loss: 0.9554 Epoch 26/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6030 - Precision: 0.5485 - Recall: 0.1245 - accuracy: 0.4458 - loss: 1.1556 Epoch 27/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6721 - Precision: 0.8047 - Recall: 0.1949 - accuracy: 0.4793 - loss: 1.0902 Epoch 28/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6723 - Precision: 0.7315 - Recall: 0.1774 - accuracy: 0.5053 - loss: 0.9808 Epoch 29/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6666 - Precision: 0.7524 - Recall: 0.1522 - accuracy: 0.4894 - loss: 1.0101 Epoch 30/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6600 - Precision: 0.8035 - Recall: 0.1632 - accuracy: 0.4886 - loss: 1.0600 Epoch 31/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6419 - Precision: 0.8082 - Recall: 0.1150 - accuracy: 0.4726 - loss: 1.0099 Epoch 32/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6343 - Precision: 0.7457 - Recall: 0.1422 - accuracy: 0.4735 - loss: 1.0501 Epoch 33/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6595 - Precision: 0.7434 - Recall: 0.1492 - accuracy: 0.4913 - loss: 1.0158 Epoch 34/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6477 - Precision: 0.7765 - Recall: 0.1589 - accuracy: 0.4845 - loss: 1.0078 Epoch 35/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6443 - Precision: 0.6687 - Recall: 0.1344 - accuracy: 0.4865 - loss: 1.1581 Epoch 36/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6224 - Precision: 0.6551 - Recall: 0.1027 - accuracy: 0.4695 - loss: 1.1966 Epoch 37/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6705 - Precision: 0.7822 - Recall: 0.1531 - accuracy: 0.5029 - loss: 1.0107 Epoch 38/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6406 - Precision: 0.7851 - Recall: 0.1122 - accuracy: 0.4675 - loss: 1.0530 Epoch 39/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6693 - Precision: 0.7882 - Recall: 0.1460 - accuracy: 0.5001 - loss: 1.0315 Epoch 40/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6331 - Precision: 0.7154 - Recall: 0.1067 - accuracy: 0.4801 - loss: 1.0392 Epoch 41/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6327 - Precision: 0.6480 - Recall: 0.1145 - accuracy: 0.4798 - loss: 1.0494 Epoch 42/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6262 - Precision: 0.7210 - Recall: 0.0979 - accuracy: 0.4641 - loss: 1.0504 Epoch 43/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6417 - Precision: 0.7188 - Recall: 0.0770 - accuracy: 0.4897 - loss: 1.0732 Epoch 44/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6068 - Precision: 0.7649 - Recall: 0.0371 - accuracy: 0.4661 - loss: 1.0586 Epoch 45/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6300 - Precision: 0.7658 - Recall: 0.0578 - accuracy: 0.4802 - loss: 1.0355 Epoch 46/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6508 - Precision: 0.8532 - Recall: 0.1032 - accuracy: 0.5000 - loss: 1.0233 Epoch 47/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.7016 - Precision: 0.8517 - Recall: 0.1205 - accuracy: 0.5465 - loss: 0.9928 Epoch 48/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6076 - Precision: 0.7586 - Recall: 0.0827 - accuracy: 0.4683 - loss: 1.0580 Epoch 49/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6214 - Precision: 0.6964 - Recall: 0.0973 - accuracy: 0.4661 - loss: 1.0961 Epoch 50/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6504 - Precision: 0.8386 - Recall: 0.1023 - accuracy: 0.4953 - loss: 1.0150 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 37ms/step Epoch 1/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 17s 6ms/step - AUC: 0.5035 - Precision: 0.3359 - Recall: 0.2779 - accuracy: 0.3432 - loss: 3.4301 Epoch 2/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.5537 - Precision: 0.3910 - Recall: 0.2338 - accuracy: 0.4191 - loss: 1.5824 Epoch 3/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6046 - Precision: 0.4429 - Recall: 0.1864 - accuracy: 0.4316 - loss: 1.2116 Epoch 4/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6123 - Precision: 0.4882 - Recall: 0.2138 - accuracy: 0.4544 - loss: 1.1584 Epoch 5/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5929 - Precision: 0.5196 - Recall: 0.1439 - accuracy: 0.4372 - loss: 1.1115 Epoch 6/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5796 - Precision: 0.4134 - Recall: 0.1104 - accuracy: 0.4428 - loss: 1.1275 Epoch 7/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6046 - Precision: 0.4710 - Recall: 0.1689 - accuracy: 0.4579 - loss: 1.1010 Epoch 8/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6351 - Precision: 0.5656 - Recall: 0.2196 - accuracy: 0.4960 - loss: 1.0858 Epoch 9/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6619 - Precision: 0.6371 - Recall: 0.1780 - accuracy: 0.5127 - loss: 1.0237 Epoch 10/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6223 - Precision: 0.5293 - Recall: 0.1568 - accuracy: 0.4782 - loss: 1.0585 Epoch 11/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6588 - Precision: 0.5534 - Recall: 0.1607 - accuracy: 0.4912 - loss: 1.0411 Epoch 12/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6302 - Precision: 0.5889 - Recall: 0.1256 - accuracy: 0.4976 - loss: 1.0352 Epoch 13/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6440 - Precision: 0.6396 - Recall: 0.1411 - accuracy: 0.4782 - loss: 1.0266 Epoch 14/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6727 - Precision: 0.7039 - Recall: 0.2247 - accuracy: 0.5290 - loss: 1.0249 Epoch 15/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6931 - Precision: 0.7344 - Recall: 0.1960 - accuracy: 0.5230 - loss: 0.9931 Epoch 16/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6333 - Precision: 0.6276 - Recall: 0.1662 - accuracy: 0.4712 - loss: 1.0297 Epoch 17/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6634 - Precision: 0.6313 - Recall: 0.1610 - accuracy: 0.4968 - loss: 1.0162 Epoch 18/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6605 - Precision: 0.7180 - Recall: 0.2100 - accuracy: 0.4664 - loss: 1.0464 Epoch 19/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6378 - Precision: 0.6474 - Recall: 0.1706 - accuracy: 0.4580 - loss: 1.0497 Epoch 20/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.7042 - Precision: 0.7276 - Recall: 0.2280 - accuracy: 0.5127 - loss: 0.9618 Epoch 21/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6187 - Precision: 0.6450 - Recall: 0.1371 - accuracy: 0.4108 - loss: 1.0344 Epoch 22/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.7073 - Precision: 0.7172 - Recall: 0.2653 - accuracy: 0.5200 - loss: 0.9699 Epoch 23/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6850 - Precision: 0.7650 - Recall: 0.2216 - accuracy: 0.5001 - loss: 0.9714 Epoch 24/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.7129 - Precision: 0.8380 - Recall: 0.2519 - accuracy: 0.4956 - loss: 0.9281 Epoch 25/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6598 - Precision: 0.7240 - Recall: 0.1749 - accuracy: 0.4768 - loss: 1.0909 Epoch 26/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7149 - Precision: 0.8541 - Recall: 0.2645 - accuracy: 0.5118 - loss: 0.9302 Epoch 27/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7182 - Precision: 0.7756 - Recall: 0.2571 - accuracy: 0.5168 - loss: 0.9680 Epoch 28/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7246 - Precision: 0.8172 - Recall: 0.2695 - accuracy: 0.4998 - loss: 0.9540 Epoch 29/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7028 - Precision: 0.8121 - Recall: 0.2540 - accuracy: 0.4839 - loss: 0.9046 Epoch 30/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6967 - Precision: 0.7972 - Recall: 0.2480 - accuracy: 0.4784 - loss: 0.9447 Epoch 31/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6924 - Precision: 0.8480 - Recall: 0.2529 - accuracy: 0.4659 - loss: 0.9559 Epoch 32/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6737 - Precision: 0.7964 - Recall: 0.1862 - accuracy: 0.4693 - loss: 0.9772 Epoch 33/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7096 - Precision: 0.8059 - Recall: 0.2429 - accuracy: 0.5066 - loss: 0.9375 Epoch 34/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6899 - Precision: 0.8206 - Recall: 0.1959 - accuracy: 0.4961 - loss: 0.9524 Epoch 35/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7099 - Precision: 0.8441 - Recall: 0.2465 - accuracy: 0.5100 - loss: 0.9785 Epoch 36/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7088 - Precision: 0.8357 - Recall: 0.2409 - accuracy: 0.4745 - loss: 0.9462 Epoch 37/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7073 - Precision: 0.9398 - Recall: 0.2179 - accuracy: 0.4893 - loss: 0.9019 Epoch 38/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7206 - Precision: 0.8992 - Recall: 0.2434 - accuracy: 0.5164 - loss: 0.9079 Epoch 39/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7180 - Precision: 0.8767 - Recall: 0.2419 - accuracy: 0.5072 - loss: 0.8922 Epoch 40/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6994 - Precision: 0.8883 - Recall: 0.2472 - accuracy: 0.5074 - loss: 0.9589 Epoch 41/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7194 - Precision: 0.8697 - Recall: 0.2732 - accuracy: 0.4966 - loss: 0.9675 Epoch 42/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6912 - Precision: 0.8931 - Recall: 0.2675 - accuracy: 0.4818 - loss: 0.9612 Epoch 43/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.7011 - Precision: 0.8455 - Recall: 0.2292 - accuracy: 0.4799 - loss: 0.9075 Epoch 44/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6755 - Precision: 0.8260 - Recall: 0.2243 - accuracy: 0.4578 - loss: 0.9547 Epoch 45/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7198 - Precision: 0.9160 - Recall: 0.2671 - accuracy: 0.4834 - loss: 0.8587 Epoch 46/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6873 - Precision: 0.8874 - Recall: 0.2189 - accuracy: 0.4856 - loss: 1.0424 Epoch 47/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.7142 - Precision: 0.9098 - Recall: 0.2520 - accuracy: 0.4998 - loss: 0.9257 Epoch 48/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7094 - Precision: 0.9045 - Recall: 0.2484 - accuracy: 0.5072 - loss: 0.8910 Epoch 49/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.7117 - Precision: 0.9685 - Recall: 0.2711 - accuracy: 0.4679 - loss: 0.8523 Epoch 50/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7224 - Precision: 0.9505 - Recall: 0.2384 - accuracy: 0.5271 - loss: 0.9340 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step Epoch 1/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 7s 6ms/step - AUC: 0.5442 - Precision: 0.4525 - Recall: 0.2025 - accuracy: 0.3772 - loss: 3.4163 Epoch 2/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6046 - Precision: 0.4660 - Recall: 0.2133 - accuracy: 0.5021 - loss: 1.0672 Epoch 3/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6198 - Precision: 0.4341 - Recall: 0.1927 - accuracy: 0.5050 - loss: 1.0885 Epoch 4/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6446 - Precision: 0.4584 - Recall: 0.2154 - accuracy: 0.5107 - loss: 1.0384 Epoch 5/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6478 - Precision: 0.4895 - Recall: 0.2481 - accuracy: 0.5092 - loss: 1.0401 Epoch 6/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6062 - Precision: 0.3978 - Recall: 0.0994 - accuracy: 0.4797 - loss: 1.0633 Epoch 7/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5990 - Precision: 0.3690 - Recall: 0.1638 - accuracy: 0.4369 - loss: 1.0774 Epoch 8/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5916 - Precision: 0.3688 - Recall: 0.0999 - accuracy: 0.4782 - loss: 1.0741 Epoch 9/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6330 - Precision: 0.5369 - Recall: 0.3201 - accuracy: 0.5054 - loss: 1.0532 Epoch 10/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6046 - Precision: 0.4212 - Recall: 0.2286 - accuracy: 0.5124 - loss: 1.0560 Epoch 11/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6241 - Precision: 0.4123 - Recall: 0.2181 - accuracy: 0.5037 - loss: 1.0489 Epoch 12/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5977 - Precision: 0.3765 - Recall: 0.1350 - accuracy: 0.4481 - loss: 1.0764 Epoch 13/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5972 - Precision: 0.4067 - Recall: 0.1146 - accuracy: 0.4833 - loss: 1.0866 Epoch 14/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5928 - Precision: 0.4726 - Recall: 0.2418 - accuracy: 0.4862 - loss: 1.9670 Epoch 15/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5809 - Precision: 0.3844 - Recall: 0.1311 - accuracy: 0.4532 - loss: 1.0914 Epoch 16/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6069 - Precision: 0.4612 - Recall: 0.2192 - accuracy: 0.4905 - loss: 1.0642 Epoch 17/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6070 - Precision: 0.4190 - Recall: 0.1489 - accuracy: 0.4869 - loss: 1.0721 Epoch 18/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5946 - Precision: 0.4772 - Recall: 0.2892 - accuracy: 0.4752 - loss: 1.5422 Epoch 19/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6143 - Precision: 0.4226 - Recall: 0.1938 - accuracy: 0.4790 - loss: 1.0751 Epoch 20/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5899 - Precision: 0.4694 - Recall: 0.2052 - accuracy: 0.4817 - loss: 1.0684 Epoch 21/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6332 - Precision: 0.5341 - Recall: 0.3745 - accuracy: 0.5266 - loss: 1.0472 Epoch 22/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6209 - Precision: 0.4184 - Recall: 0.2132 - accuracy: 0.5287 - loss: 3.4494 Epoch 23/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6099 - Precision: 0.4282 - Recall: 0.1954 - accuracy: 0.4839 - loss: 1.0643 Epoch 24/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6279 - Precision: 0.4918 - Recall: 0.2248 - accuracy: 0.5151 - loss: 1.2806 Epoch 25/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6163 - Precision: 0.4872 - Recall: 0.1491 - accuracy: 0.4870 - loss: 1.0762 Epoch 26/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6087 - Precision: 0.4877 - Recall: 0.2508 - accuracy: 0.5067 - loss: 1.0484 Epoch 27/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6132 - Precision: 0.4034 - Recall: 0.1779 - accuracy: 0.4933 - loss: 1.0625 Epoch 28/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5849 - Precision: 0.3686 - Recall: 0.1174 - accuracy: 0.4259 - loss: 1.0803 Epoch 29/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5672 - Precision: 0.4154 - Recall: 0.1999 - accuracy: 0.4539 - loss: 1.1273 Epoch 30/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5865 - Precision: 0.4638 - Recall: 0.2595 - accuracy: 0.4327 - loss: 1.0971 Epoch 31/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6038 - Precision: 0.4811 - Recall: 0.2602 - accuracy: 0.4894 - loss: 1.0656 Epoch 32/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6177 - Precision: 0.5062 - Recall: 0.3371 - accuracy: 0.5080 - loss: 1.0529 Epoch 33/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6040 - Precision: 0.2191 - Recall: 0.0354 - accuracy: 0.4897 - loss: 1.0560 Epoch 34/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6379 - Precision: 0.5408 - Recall: 0.4135 - accuracy: 0.5285 - loss: 1.0341 Epoch 35/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6356 - Precision: 0.4598 - Recall: 0.1896 - accuracy: 0.4954 - loss: 1.0496 Epoch 36/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6330 - Precision: 0.4837 - Recall: 0.2768 - accuracy: 0.5307 - loss: 1.0424 Epoch 37/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6162 - Precision: 0.4279 - Recall: 0.1784 - accuracy: 0.4977 - loss: 1.0561 Epoch 38/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5870 - Precision: 0.3134 - Recall: 0.0861 - accuracy: 0.4707 - loss: 1.0709 Epoch 39/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6173 - Precision: 0.4944 - Recall: 0.2568 - accuracy: 0.5024 - loss: 1.0676 Epoch 40/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6367 - Precision: 0.5047 - Recall: 0.3252 - accuracy: 0.5119 - loss: 1.0441 Epoch 41/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5895 - Precision: 0.3839 - Recall: 0.1817 - accuracy: 0.4873 - loss: 1.0622 Epoch 42/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6125 - Precision: 0.5159 - Recall: 0.3910 - accuracy: 0.5023 - loss: 1.0535 Epoch 43/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6089 - Precision: 0.4698 - Recall: 0.3013 - accuracy: 0.4954 - loss: 1.0685 Epoch 44/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6010 - Precision: 0.4802 - Recall: 0.2779 - accuracy: 0.4867 - loss: 1.0605 Epoch 45/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6150 - Precision: 0.4896 - Recall: 0.2387 - accuracy: 0.5018 - loss: 1.0561 Epoch 46/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6224 - Precision: 0.4492 - Recall: 0.1894 - accuracy: 0.4995 - loss: 1.0495 Epoch 47/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6074 - Precision: 0.3835 - Recall: 0.1241 - accuracy: 0.4829 - loss: 1.0618 Epoch 48/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6087 - Precision: 0.4034 - Recall: 0.1721 - accuracy: 0.5045 - loss: 1.0559 Epoch 49/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6075 - Precision: 0.4157 - Recall: 0.1177 - accuracy: 0.4871 - loss: 1.0593 Epoch 50/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6081 - Precision: 0.3999 - Recall: 0.1520 - accuracy: 0.4875 - loss: 1.0580 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 27ms/step Epoch 1/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 5s 6ms/step - AUC: 0.5321 - Precision: 0.3573 - Recall: 0.1871 - accuracy: 0.3650 - loss: 2.5484 Epoch 2/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5875 - Precision: 0.4240 - Recall: 0.1648 - accuracy: 0.4708 - loss: 1.1224 Epoch 3/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5853 - Precision: 0.4637 - Recall: 0.2370 - accuracy: 0.4778 - loss: 1.1239 Epoch 4/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6160 - Precision: 0.4537 - Recall: 0.2940 - accuracy: 0.5068 - loss: 1.0820 Epoch 5/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5906 - Precision: 0.3453 - Recall: 0.1581 - accuracy: 0.4832 - loss: 1.0711 Epoch 6/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6191 - Precision: 0.2262 - Recall: 0.0555 - accuracy: 0.4985 - loss: 1.0531 Epoch 7/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6403 - Precision: 0.4197 - Recall: 0.1701 - accuracy: 0.5145 - loss: 1.0446 Epoch 8/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6003 - Precision: 0.5134 - Recall: 0.3313 - accuracy: 0.4981 - loss: 1.0495 Epoch 9/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6172 - Precision: 0.4975 - Recall: 0.2805 - accuracy: 0.4983 - loss: 1.0639 Epoch 10/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6429 - Precision: 0.5176 - Recall: 0.3864 - accuracy: 0.5157 - loss: 1.0328 Epoch 11/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6007 - Precision: 0.4728 - Recall: 0.2904 - accuracy: 0.4828 - loss: 1.0768 Epoch 12/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6226 - Precision: 0.4214 - Recall: 0.2236 - accuracy: 0.4931 - loss: 1.0531 Epoch 13/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6007 - Precision: 0.4840 - Recall: 0.2312 - accuracy: 0.4922 - loss: 1.0592 Epoch 14/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6242 - Precision: 0.4765 - Recall: 0.2938 - accuracy: 0.5099 - loss: 1.0385 Epoch 15/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5996 - Precision: 0.3783 - Recall: 0.1288 - accuracy: 0.4654 - loss: 1.0740 Epoch 16/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5981 - Precision: 0.2999 - Recall: 0.0960 - accuracy: 0.4644 - loss: 1.0697 Epoch 17/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5625 - Precision: 0.2620 - Recall: 0.0456 - accuracy: 0.4564 - loss: 1.0889 Epoch 18/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5976 - Precision: 0.4745 - Recall: 0.2608 - accuracy: 0.4768 - loss: 1.0796 Epoch 19/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6345 - Precision: 0.5213 - Recall: 0.4809 - accuracy: 0.5162 - loss: 1.0425 Epoch 20/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6228 - Precision: 0.3623 - Recall: 0.1420 - accuracy: 0.5053 - loss: 1.0742 Epoch 21/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6380 - Precision: 0.4662 - Recall: 0.2768 - accuracy: 0.5225 - loss: 1.0439 Epoch 22/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5864 - Precision: 0.2928 - Recall: 0.0923 - accuracy: 0.4609 - loss: 1.0717 Epoch 23/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6109 - Precision: 0.5015 - Recall: 0.2499 - accuracy: 0.4905 - loss: 1.0496 Epoch 24/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5829 - Precision: 0.4445 - Recall: 0.2725 - accuracy: 0.4683 - loss: 1.0871 Epoch 25/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6419 - Precision: 0.5313 - Recall: 0.4133 - accuracy: 0.5231 - loss: 1.0260 Epoch 26/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6415 - Precision: 0.4528 - Recall: 0.2083 - accuracy: 0.5321 - loss: 1.0355 Epoch 27/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6130 - Precision: 0.3348 - Recall: 0.1432 - accuracy: 0.4901 - loss: 1.0495 Epoch 28/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6078 - Precision: 0.3566 - Recall: 0.1353 - accuracy: 0.4843 - loss: 1.0606 Epoch 29/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6149 - Precision: 0.4368 - Recall: 0.2285 - accuracy: 0.4781 - loss: 1.0668 Epoch 30/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5830 - Precision: 0.4475 - Recall: 0.2507 - accuracy: 0.4743 - loss: 1.1057 Epoch 31/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5919 - Precision: 0.4525 - Recall: 0.2432 - accuracy: 0.4748 - loss: 1.0719 Epoch 32/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5975 - Precision: 0.4725 - Recall: 0.2213 - accuracy: 0.4799 - loss: 1.0674 Epoch 33/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6158 - Precision: 0.4522 - Recall: 0.2133 - accuracy: 0.4942 - loss: 1.0553 Epoch 34/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6166 - Precision: 0.4977 - Recall: 0.4263 - accuracy: 0.5027 - loss: 1.0476 Epoch 35/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6011 - Precision: 0.4642 - Recall: 0.2993 - accuracy: 0.4983 - loss: 1.1076 Epoch 36/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5811 - Precision: 0.3424 - Recall: 0.1363 - accuracy: 0.4761 - loss: 1.0683 Epoch 37/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6038 - Precision: 0.4689 - Recall: 0.2162 - accuracy: 0.4780 - loss: 1.0602 Epoch 38/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6009 - Precision: 0.4579 - Recall: 0.2612 - accuracy: 0.4783 - loss: 1.0651 Epoch 39/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6481 - Precision: 0.5353 - Recall: 0.4279 - accuracy: 0.5283 - loss: 1.0252 Epoch 40/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6067 - Precision: 0.4770 - Recall: 0.3620 - accuracy: 0.4957 - loss: 1.0517 Epoch 41/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6044 - Precision: 0.1541 - Recall: 0.0231 - accuracy: 0.4722 - loss: 1.0623 Epoch 42/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6137 - Precision: 0.4380 - Recall: 0.1737 - accuracy: 0.4931 - loss: 1.0553 Epoch 43/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6085 - Precision: 0.3778 - Recall: 0.1464 - accuracy: 0.5132 - loss: 1.0450 Epoch 44/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6139 - Precision: 0.3388 - Recall: 0.1248 - accuracy: 0.4724 - loss: 1.0644 Epoch 45/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6494 - Precision: 0.5026 - Recall: 0.4103 - accuracy: 0.5358 - loss: 1.0168 Epoch 46/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6120 - Precision: 0.2588 - Recall: 0.0573 - accuracy: 0.4937 - loss: 1.0594 Epoch 47/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6009 - Precision: 0.5496 - Recall: 0.1429 - accuracy: 0.4999 - loss: 1.0547 Epoch 48/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.5948 - Precision: 0.3256 - Recall: 0.0909 - accuracy: 0.4861 - loss: 1.0699 Epoch 49/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6170 - Precision: 0.3996 - Recall: 0.1902 - accuracy: 0.5010 - loss: 1.0540 Epoch 50/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.5852 - Precision: 0.4753 - Recall: 0.3453 - accuracy: 0.4789 - loss: 1.0729 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 53ms/step Epoch 1/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 5s 6ms/step - AUC: 0.5992 - Precision: 0.4878 - Recall: 0.3126 - accuracy: 0.4138 - loss: 2.1886 Epoch 2/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6259 - Precision: 0.5316 - Recall: 0.1817 - accuracy: 0.4867 - loss: 1.6743 Epoch 3/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6317 - Precision: 0.4289 - Recall: 0.1205 - accuracy: 0.5137 - loss: 1.1174 Epoch 4/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6237 - Precision: 0.4280 - Recall: 0.0991 - accuracy: 0.4998 - loss: 1.0596 Epoch 5/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6077 - Precision: 0.7231 - Recall: 0.0515 - accuracy: 0.4625 - loss: 1.0640 Epoch 6/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6167 - Precision: 0.4778 - Recall: 0.1791 - accuracy: 0.4868 - loss: 1.1496 Epoch 7/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6151 - Precision: 0.4761 - Recall: 0.2651 - accuracy: 0.4774 - loss: 1.4066 Epoch 8/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5978 - Precision: 0.4707 - Recall: 0.3536 - accuracy: 0.4828 - loss: 1.0694 Epoch 9/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5933 - Precision: 0.4442 - Recall: 0.1819 - accuracy: 0.4962 - loss: 1.0693 Epoch 10/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6172 - Precision: 0.4045 - Recall: 0.2128 - accuracy: 0.5180 - loss: 1.0428 Epoch 11/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5833 - Precision: 0.0704 - Recall: 0.0051 - accuracy: 0.4783 - loss: 1.0685 Epoch 12/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5936 - Precision: 0.4606 - Recall: 0.3460 - accuracy: 0.4756 - loss: 1.0749 Epoch 13/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6182 - Precision: 0.0605 - Recall: 0.0032 - accuracy: 0.5051 - loss: 1.0424 Epoch 14/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6194 - Precision: 0.5018 - Recall: 0.3404 - accuracy: 0.5039 - loss: 1.0426 Epoch 15/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5921 - Precision: 0.3906 - Recall: 0.1468 - accuracy: 0.4841 - loss: 1.0586 Epoch 16/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6025 - Precision: 0.2821 - Recall: 0.1036 - accuracy: 0.4913 - loss: 1.0496 Epoch 17/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6108 - Precision: 0.2184 - Recall: 0.0605 - accuracy: 0.4862 - loss: 1.0592 Epoch 18/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5710 - Precision: 0.2357 - Recall: 0.0736 - accuracy: 0.4607 - loss: 1.0820 Epoch 19/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6100 - Precision: 0.5056 - Recall: 0.4611 - accuracy: 0.5058 - loss: 1.0410 Epoch 20/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6281 - Precision: 0.3024 - Recall: 0.1145 - accuracy: 0.4953 - loss: 1.0495 Epoch 21/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5932 - Precision: 0.2682 - Recall: 0.0848 - accuracy: 0.4697 - loss: 1.0741 Epoch 22/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6076 - Precision: 0.4708 - Recall: 0.2615 - accuracy: 0.4992 - loss: 1.0497 Epoch 23/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6208 - Precision: 0.3117 - Recall: 0.1206 - accuracy: 0.4993 - loss: 1.0422 Epoch 24/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6021 - Precision: 0.2902 - Recall: 0.0959 - accuracy: 0.4217 - loss: 1.0682 Epoch 25/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6085 - Precision: 0.4436 - Recall: 0.2590 - accuracy: 0.4844 - loss: 1.0544 Epoch 26/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6105 - Precision: 0.4656 - Recall: 0.2269 - accuracy: 0.4890 - loss: 1.0532 Epoch 27/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5905 - Precision: 0.4650 - Recall: 0.2346 - accuracy: 0.4880 - loss: 1.0555 Epoch 28/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5856 - Precision: 0.4584 - Recall: 0.2570 - accuracy: 0.4763 - loss: 1.0640 Epoch 29/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6060 - Precision: 0.4811 - Recall: 0.2158 - accuracy: 0.4934 - loss: 1.0550 Epoch 30/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6211 - Precision: 0.3611 - Recall: 0.0784 - accuracy: 0.4956 - loss: 1.0501 Epoch 31/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6034 - Precision: 0.4172 - Recall: 0.1490 - accuracy: 0.4726 - loss: 1.06510 Epoch 32/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.5937 - Precision: 0.4322 - Recall: 0.2250 - accuracy: 0.4684 - loss: 1.0870 Epoch 33/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6082 - Precision: 0.4695 - Recall: 0.3190 - accuracy: 0.5000 - loss: 1.0586 Epoch 34/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6122 - Precision: 0.4220 - Recall: 0.2179 - accuracy: 0.4940 - loss: 1.0497 Epoch 35/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6261 - Precision: 0.4592 - Recall: 0.2765 - accuracy: 0.5203 - loss: 1.0460 Epoch 36/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.6088 - Precision: 0.3366 - Recall: 0.1510 - accuracy: 0.4782 - loss: 1.0590 Epoch 37/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6302 - Precision: 0.4277 - Recall: 0.2706 - accuracy: 0.4904 - loss: 1.0463 Epoch 38/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6086 - Precision: 0.3168 - Recall: 0.1413 - accuracy: 0.4852 - loss: 1.0539 Epoch 39/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6166 - Precision: 0.4812 - Recall: 0.1404 - accuracy: 0.4955 - loss: 1.0558 Epoch 40/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5970 - Precision: 0.2299 - Recall: 0.0703 - accuracy: 0.4655 - loss: 1.0701 Epoch 41/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6204 - Precision: 0.5110 - Recall: 0.2490 - accuracy: 0.4844 - loss: 1.0545 Epoch 42/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6232 - Precision: 0.4816 - Recall: 0.2622 - accuracy: 0.4874 - loss: 1.0567 Epoch 43/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5611 - Precision: 0.4088 - Recall: 0.1888 - accuracy: 0.4437 - loss: 1.0941 Epoch 44/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6052 - Precision: 0.4650 - Recall: 0.3064 - accuracy: 0.4755 - loss: 1.0669 Epoch 45/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6174 - Precision: 0.3600 - Recall: 0.0777 - accuracy: 0.5107 - loss: 1.0435 Epoch 46/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6474 - Precision: 0.4750 - Recall: 0.3301 - accuracy: 0.5414 - loss: 1.0189 Epoch 47/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5861 - Precision: 0.3258 - Recall: 0.0948 - accuracy: 0.4986 - loss: 1.0678 Epoch 48/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.6038 - Precision: 0.4470 - Recall: 0.2666 - accuracy: 0.5057 - loss: 1.0451 Epoch 49/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5892 - Precision: 0.2689 - Recall: 0.0980 - accuracy: 0.4748 - loss: 1.0609 Epoch 50/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6327 - Precision: 0.2702 - Recall: 0.0908 - accuracy: 0.5118 - loss: 1.0402 5/5 ━━━━━━━━━━━━━━━━━━━━ 1s 71ms/step Epoch 1/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 6s 7ms/step - AUC: 0.5565 - Precision: 0.4136 - Recall: 0.2635 - accuracy: 0.4113 - loss: 8.8693 Epoch 2/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6260 - Precision: 0.5236 - Recall: 0.2009 - accuracy: 0.4934 - loss: 3.0863 Epoch 3/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6144 - Precision: 0.4270 - Recall: 0.1920 - accuracy: 0.5107 - loss: 1.5445 Epoch 4/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6288 - Precision: 0.5268 - Recall: 0.3799 - accuracy: 0.4927 - loss: 2.1038 Epoch 5/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6176 - Precision: 0.4734 - Recall: 0.2140 - accuracy: 0.4899 - loss: 3.1784 Epoch 6/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6054 - Precision: 0.4551 - Recall: 0.1929 - accuracy: 0.4711 - loss: 1.2548 Epoch 7/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6054 - Precision: 0.4409 - Recall: 0.1700 - accuracy: 0.4282 - loss: 1.0588 Epoch 8/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5958 - Precision: 0.4188 - Recall: 0.1555 - accuracy: 0.4684 - loss: 1.0749 Epoch 9/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5684 - Precision: 0.3538 - Recall: 0.1285 - accuracy: 0.4264 - loss: 1.0926 Epoch 10/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5889 - Precision: 0.4898 - Recall: 0.2761 - accuracy: 0.4525 - loss: 1.0798 Epoch 11/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6141 - Precision: 0.4316 - Recall: 0.1841 - accuracy: 0.4394 - loss: 1.0666 Epoch 12/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5907 - Precision: 0.4598 - Recall: 0.2715 - accuracy: 0.4763 - loss: 1.0778 Epoch 13/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5841 - Precision: 0.4571 - Recall: 0.2376 - accuracy: 0.4646 - loss: 1.9033 Epoch 14/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6015 - Precision: 0.4809 - Recall: 0.3098 - accuracy: 0.5021 - loss: 1.0977 Epoch 15/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6270 - Precision: 0.3165 - Recall: 0.0919 - accuracy: 0.4842 - loss: 1.0490 Epoch 16/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5878 - Precision: 0.3989 - Recall: 0.1611 - accuracy: 0.4360 - loss: 1.0717 Epoch 17/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5731 - Precision: 0.4203 - Recall: 0.1790 - accuracy: 0.4542 - loss: 1.0902 Epoch 18/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5902 - Precision: 0.4673 - Recall: 0.3570 - accuracy: 0.4800 - loss: 1.0774 Epoch 19/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6069 - Precision: 0.4209 - Recall: 0.0588 - accuracy: 0.4843 - loss: 1.0612 Epoch 20/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5991 - Precision: 0.4614 - Recall: 0.3038 - accuracy: 0.4933 - loss: 1.0703 Epoch 21/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6010 - Precision: 0.3490 - Recall: 0.0887 - accuracy: 0.5014 - loss: 1.0580 Epoch 22/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6078 - Precision: 0.4486 - Recall: 0.1869 - accuracy: 0.4993 - loss: 1.0673 Epoch 23/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5938 - Precision: 0.4550 - Recall: 0.2406 - accuracy: 0.4860 - loss: 1.0673 Epoch 24/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6002 - Precision: 0.4307 - Recall: 0.2479 - accuracy: 0.4933 - loss: 1.0667 Epoch 25/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5886 - Precision: 0.3573 - Recall: 0.0948 - accuracy: 0.4676 - loss: 1.0788 Epoch 26/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6171 - Precision: 0.4883 - Recall: 0.3252 - accuracy: 0.4993 - loss: 1.0618 Epoch 27/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6222 - Precision: 0.4578 - Recall: 0.2759 - accuracy: 0.4868 - loss: 1.0530 Epoch 28/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6248 - Precision: 0.5069 - Recall: 0.3340 - accuracy: 0.4472 - loss: 1.0583 Epoch 29/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5983 - Precision: 0.4349 - Recall: 0.1620 - accuracy: 0.4787 - loss: 3.8202 Epoch 30/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6263 - Precision: 0.5190 - Recall: 0.3858 - accuracy: 0.5020 - loss: 1.0584 Epoch 31/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6051 - Precision: 0.4783 - Recall: 0.3342 - accuracy: 0.5245 - loss: 1.0548 Epoch 32/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6243 - Precision: 0.4323 - Recall: 0.1704 - accuracy: 0.5141 - loss: 1.0556 Epoch 33/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6216 - Precision: 0.4893 - Recall: 0.2397 - accuracy: 0.4993 - loss: 1.4362 Epoch 34/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5954 - Precision: 0.4949 - Recall: 0.1109 - accuracy: 0.4709 - loss: 1.0675 Epoch 35/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6287 - Precision: 0.4891 - Recall: 0.2625 - accuracy: 0.5109 - loss: 1.0389 Epoch 36/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6089 - Precision: 0.4724 - Recall: 0.2737 - accuracy: 0.5054 - loss: 1.0584 Epoch 37/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6244 - Precision: 0.4202 - Recall: 0.1925 - accuracy: 0.5010 - loss: 1.0546 Epoch 38/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6011 - Precision: 0.4889 - Recall: 0.3360 - accuracy: 0.5022 - loss: 1.0602 Epoch 39/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5856 - Precision: 0.4056 - Recall: 0.1979 - accuracy: 0.4502 - loss: 1.0706 Epoch 40/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6375 - Precision: 0.4810 - Recall: 0.2835 - accuracy: 0.5287 - loss: 1.0330 Epoch 41/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5934 - Precision: 0.3680 - Recall: 0.1338 - accuracy: 0.4687 - loss: 1.0740 Epoch 42/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6269 - Precision: 0.4470 - Recall: 0.1583 - accuracy: 0.4960 - loss: 1.0548 Epoch 43/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6302 - Precision: 0.4963 - Recall: 0.2919 - accuracy: 0.5089 - loss: 1.0597 Epoch 44/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5966 - Precision: 0.4042 - Recall: 0.1481 - accuracy: 0.4913 - loss: 1.0628 Epoch 45/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6112 - Precision: 0.4917 - Recall: 0.3007 - accuracy: 0.5206 - loss: 1.0509 Epoch 46/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6472 - Precision: 0.4466 - Recall: 0.2163 - accuracy: 0.5102 - loss: 1.0391 Epoch 47/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6218 - Precision: 0.5044 - Recall: 0.3482 - accuracy: 0.5185 - loss: 1.0428 Epoch 48/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6252 - Precision: 0.4503 - Recall: 0.2585 - accuracy: 0.5052 - loss: 1.0550 Epoch 49/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6114 - Precision: 0.4903 - Recall: 0.2832 - accuracy: 0.4988 - loss: 1.0727 Epoch 50/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6024 - Precision: 0.4191 - Recall: 0.1875 - accuracy: 0.4785 - loss: 1.9084 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step Epoch 1/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 5s 7ms/step - AUC: 0.5497 - Precision: 0.4026 - Recall: 0.3224 - accuracy: 0.4085 - loss: 5.2218 Epoch 2/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5996 - Precision: 0.4180 - Recall: 0.0449 - accuracy: 0.4889 - loss: 1.2320 Epoch 3/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6369 - Precision: 0.5414 - Recall: 0.3385 - accuracy: 0.5237 - loss: 1.4395 Epoch 4/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6252 - Precision: 0.5195 - Recall: 0.3726 - accuracy: 0.5105 - loss: 1.5043 Epoch 5/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6322 - Precision: 0.4608 - Recall: 0.2669 - accuracy: 0.5152 - loss: 1.1478 Epoch 6/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5877 - Precision: 0.4193 - Recall: 0.1139 - accuracy: 0.4786 - loss: 1.0782 Epoch 7/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6323 - Precision: 0.5296 - Recall: 0.3574 - accuracy: 0.5123 - loss: 1.0303 Epoch 8/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6237 - Precision: 0.4928 - Recall: 0.3629 - accuracy: 0.5078 - loss: 1.4039 Epoch 9/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6026 - Precision: 0.3474 - Recall: 0.1305 - accuracy: 0.4674 - loss: 2.4843 Epoch 10/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6045 - Precision: 0.3723 - Recall: 0.1826 - accuracy: 0.4906 - loss: 1.0543 Epoch 11/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5705 - Precision: 0.3191 - Recall: 0.0867 - accuracy: 0.4733 - loss: 1.1848 Epoch 12/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6038 - Precision: 0.4650 - Recall: 0.2935 - accuracy: 0.5067 - loss: 1.0481 Epoch 13/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6010 - Precision: 0.3600 - Recall: 0.1217 - accuracy: 0.4745 - loss: 1.1116 Epoch 14/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6008 - Precision: 0.4633 - Recall: 0.2668 - accuracy: 0.4771 - loss: 1.0760 Epoch 15/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6399 - Precision: 0.4847 - Recall: 0.3058 - accuracy: 0.5361 - loss: 1.0324 Epoch 16/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6078 - Precision: 0.2316 - Recall: 0.0497 - accuracy: 0.4840 - loss: 1.0730 Epoch 17/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6266 - Precision: 0.4794 - Recall: 0.3018 - accuracy: 0.5010 - loss: 1.0436 Epoch 18/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6282 - Precision: 0.3617 - Recall: 0.1594 - accuracy: 0.5187 - loss: 1.0417 Epoch 19/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6285 - Precision: 0.4070 - Recall: 0.1842 - accuracy: 0.5048 - loss: 1.0464 Epoch 20/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6330 - Precision: 0.4169 - Recall: 0.1747 - accuracy: 0.5071 - loss: 1.0437 Epoch 21/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6004 - Precision: 0.4888 - Recall: 0.3606 - accuracy: 0.4939 - loss: 1.0580 Epoch 22/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6085 - Precision: 0.3676 - Recall: 0.1452 - accuracy: 0.4659 - loss: 1.0645 Epoch 23/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5743 - Precision: 0.2179 - Recall: 0.0402 - accuracy: 0.4739 - loss: 1.0783 Epoch 24/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6327 - Precision: 0.5219 - Recall: 0.2588 - accuracy: 0.5105 - loss: 1.0348 Epoch 25/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6120 - Precision: 0.5008 - Recall: 0.3264 - accuracy: 0.5075 - loss: 6.3290 Epoch 26/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6125 - Precision: 0.2483 - Recall: 0.0708 - accuracy: 0.4744 - loss: 1.0589 Epoch 27/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.5971 - Precision: 0.2094 - Recall: 0.0487 - accuracy: 0.4820 - loss: 1.0727 Epoch 28/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6082 - Precision: 0.4847 - Recall: 0.1568 - accuracy: 0.4882 - loss: 1.0595 Epoch 29/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6291 - Precision: 0.5207 - Recall: 0.4486 - accuracy: 0.5246 - loss: 1.0336 Epoch 30/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5891 - Precision: 0.3385 - Recall: 0.1103 - accuracy: 0.4481 - loss: 1.0724 Epoch 31/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6075 - Precision: 0.3688 - Recall: 0.1857 - accuracy: 0.4951 - loss: 1.0525 Epoch 32/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6301 - Precision: 0.4940 - Recall: 0.3088 - accuracy: 0.4913 - loss: 1.0433 Epoch 33/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6241 - Precision: 0.5392 - Recall: 0.2011 - accuracy: 0.4988 - loss: 1.0442 Epoch 34/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6033 - Precision: 0.3778 - Recall: 0.1429 - accuracy: 0.5035 - loss: 1.0602 Epoch 35/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.6165 - Precision: 0.4559 - Recall: 0.2364 - accuracy: 0.5108 - loss: 1.0538 Epoch 36/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6168 - Precision: 0.4549 - Recall: 0.2639 - accuracy: 0.4953 - loss: 1.0465 Epoch 37/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6410 - Precision: 0.5312 - Recall: 0.3293 - accuracy: 0.5199 - loss: 1.0318 Epoch 38/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6009 - Precision: 0.3534 - Recall: 0.0693 - accuracy: 0.4936 - loss: 1.0583 Epoch 39/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6170 - Precision: 0.4232 - Recall: 0.2201 - accuracy: 0.5106 - loss: 1.0408 Epoch 40/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6100 - Precision: 0.5056 - Recall: 0.2460 - accuracy: 0.4822 - loss: 1.0628 Epoch 41/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6133 - Precision: 0.5100 - Recall: 0.3605 - accuracy: 0.4849 - loss: 1.0496 Epoch 42/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6037 - Precision: 0.4150 - Recall: 0.2009 - accuracy: 0.4858 - loss: 1.0596 Epoch 43/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6058 - Precision: 0.3514 - Recall: 0.1595 - accuracy: 0.4849 - loss: 1.0581 Epoch 44/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6087 - Precision: 0.4050 - Recall: 0.1656 - accuracy: 0.5035 - loss: 1.1027 Epoch 45/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6147 - Precision: 0.4563 - Recall: 0.2281 - accuracy: 0.5122 - loss: 1.0373 Epoch 46/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6118 - Precision: 0.2791 - Recall: 0.0851 - accuracy: 0.4779 - loss: 1.0570 Epoch 47/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6033 - Precision: 0.3934 - Recall: 0.0726 - accuracy: 0.4772 - loss: 1.0610 Epoch 48/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6056 - Precision: 0.4899 - Recall: 0.3281 - accuracy: 0.4993 - loss: 1.0506 Epoch 49/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6132 - Precision: 0.4393 - Recall: 0.1714 - accuracy: 0.4954 - loss: 1.0502 Epoch 50/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6214 - Precision: 0.4858 - Recall: 0.2256 - accuracy: 0.4928 - loss: 1.0498 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 32ms/step Epoch 1/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 4s 8ms/step - AUC: 0.5669 - Precision: 0.4075 - Recall: 0.2796 - accuracy: 0.4067 - loss: 2.3423 Epoch 2/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6002 - Precision: 0.5085 - Recall: 0.3760 - accuracy: 0.4944 - loss: 1.6038 Epoch 3/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5979 - Precision: 0.3418 - Recall: 0.0271 - accuracy: 0.4947 - loss: 1.1424 Epoch 4/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6002 - Precision: 0.4592 - Recall: 0.2744 - accuracy: 0.4759 - loss: 1.1693 Epoch 5/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6024 - Precision: 0.3436 - Recall: 0.0781 - accuracy: 0.4901 - loss: 1.3648 Epoch 6/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5873 - Precision: 0.2849 - Recall: 0.1193 - accuracy: 0.4584 - loss: 1.1061 Epoch 7/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6165 - Precision: 0.4900 - Recall: 0.4202 - accuracy: 0.5010 - loss: 1.0566 Epoch 8/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6264 - Precision: 0.3042 - Recall: 0.0961 - accuracy: 0.5230 - loss: 1.0371 Epoch 9/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6276 - Precision: 0.4216 - Recall: 0.2000 - accuracy: 0.5329 - loss: 1.0412 Epoch 10/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6139 - Precision: 0.4191 - Recall: 0.2227 - accuracy: 0.5185 - loss: 1.0415 Epoch 11/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6429 - Precision: 0.3181 - Recall: 0.1163 - accuracy: 0.5427 - loss: 1.0312 Epoch 12/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6351 - Precision: 0.3544 - Recall: 0.1711 - accuracy: 0.5149 - loss: 1.0384 Epoch 13/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5869 - Precision: 0.2829 - Recall: 0.0943 - accuracy: 0.4583 - loss: 1.1629 Epoch 14/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6020 - Precision: 0.4060 - Recall: 0.1652 - accuracy: 0.4764 - loss: 1.0778 Epoch 15/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5859 - Precision: 0.4133 - Recall: 0.1333 - accuracy: 0.4658 - loss: 1.0739 Epoch 16/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6299 - Precision: 0.4804 - Recall: 0.3120 - accuracy: 0.4941 - loss: 2.0031 Epoch 17/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6293 - Precision: 0.4695 - Recall: 0.3826 - accuracy: 0.5122 - loss: 1.9764 Epoch 18/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5664 - Precision: 0.2262 - Recall: 0.0695 - accuracy: 0.4620 - loss: 1.0731 Epoch 19/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6113 - Precision: 0.4870 - Recall: 0.4251 - accuracy: 0.4854 - loss: 1.0567 Epoch 20/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6126 - Precision: 0.3692 - Recall: 0.0997 - accuracy: 0.4833 - loss: 2.0728 Epoch 21/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6317 - Precision: 0.5264 - Recall: 0.4616 - accuracy: 0.5243 - loss: 1.0352 Epoch 22/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6443 - Precision: 0.2542 - Recall: 0.0484 - accuracy: 0.5255 - loss: 1.0322 Epoch 23/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5902 - Precision: 0.1555 - Recall: 0.0296 - accuracy: 0.4587 - loss: 1.0674 Epoch 24/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6197 - Precision: 0.5123 - Recall: 0.4418 - accuracy: 0.5076 - loss: 1.0424 Epoch 25/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6334 - Precision: 0.4413 - Recall: 0.2559 - accuracy: 0.5199 - loss: 1.0876 Epoch 26/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6284 - Precision: 0.5369 - Recall: 0.2596 - accuracy: 0.5064 - loss: 1.04270 Epoch 27/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6267 - Precision: 0.3319 - Recall: 0.1247 - accuracy: 0.5220 - loss: 1.0488 Epoch 28/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6019 - Precision: 0.2913 - Recall: 0.0691 - accuracy: 0.4751 - loss: 1.0573 Epoch 29/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5906 - Precision: 0.4337 - Recall: 0.2536 - accuracy: 0.4751 - loss: 1.0706 Epoch 30/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6157 - Precision: 0.3552 - Recall: 0.1864 - accuracy: 0.4896 - loss: 1.0495 Epoch 31/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6073 - Precision: 0.1391 - Recall: 0.0242 - accuracy: 0.4976 - loss: 1.0520 Epoch 32/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5826 - Precision: 0.4510 - Recall: 0.1639 - accuracy: 0.4728 - loss: 1.0708 Epoch 33/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.5950 - Precision: 0.4518 - Recall: 0.3166 - accuracy: 0.4748 - loss: 1.0704 Epoch 34/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6401 - Precision: 0.4695 - Recall: 0.2834 - accuracy: 0.5244 - loss: 1.0292 Epoch 35/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5897 - Precision: 0.3972 - Recall: 0.2096 - accuracy: 0.4845 - loss: 1.0665 Epoch 36/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5807 - Precision: 0.3881 - Recall: 0.1930 - accuracy: 0.4538 - loss: 1.0803 Epoch 37/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5990 - Precision: 0.4449 - Recall: 0.2796 - accuracy: 0.4673 - loss: 1.0716 Epoch 38/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6172 - Precision: 0.4967 - Recall: 0.4078 - accuracy: 0.5063 - loss: 1.0414 Epoch 39/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6181 - Precision: 0.2855 - Recall: 0.1060 - accuracy: 0.5083 - loss: 1.0404 Epoch 40/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5987 - Precision: 0.2771 - Recall: 0.0870 - accuracy: 0.4735 - loss: 1.0609 Epoch 41/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5904 - Precision: 0.2938 - Recall: 0.0446 - accuracy: 0.4902 - loss: 1.0492 Epoch 42/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5888 - Precision: 0.0440 - Recall: 0.0016 - accuracy: 0.4625 - loss: 1.2599 Epoch 43/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6230 - Precision: 0.5198 - Recall: 0.4090 - accuracy: 0.5213 - loss: 1.0298 Epoch 44/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6177 - Precision: 0.3943 - Recall: 0.2087 - accuracy: 0.5220 - loss: 1.0377 Epoch 45/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6012 - Precision: 0.3106 - Recall: 0.1076 - accuracy: 0.4737 - loss: 1.0606 Epoch 46/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6297 - Precision: 0.3452 - Recall: 0.1240 - accuracy: 0.5194 - loss: 1.0378 Epoch 47/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5902 - Precision: 0.2698 - Recall: 0.0798 - accuracy: 0.4732 - loss: 1.0667 Epoch 48/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6183 - Precision: 0.4080 - Recall: 0.2150 - accuracy: 0.4900 - loss: 1.0470 Epoch 49/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6193 - Precision: 0.2532 - Recall: 0.0793 - accuracy: 0.4923 - loss: 1.0504 Epoch 50/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6221 - Precision: 0.3454 - Recall: 0.1440 - accuracy: 0.5312 - loss: 1.0279 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 26ms/step Epoch 1/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 5s 7ms/step - AUC: 0.5029 - Precision: 0.3618 - Recall: 0.3206 - accuracy: 0.3718 - loss: 52.7544 Epoch 2/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6165 - Precision: 0.5108 - Recall: 0.3498 - accuracy: 0.5013 - loss: 21.1288 Epoch 3/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6130 - Precision: 0.3168 - Recall: 0.1086 - accuracy: 0.4867 - loss: 3.8516 Epoch 4/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5979 - Precision: 0.4566 - Recall: 0.2127 - accuracy: 0.4525 - loss: 1.9302 Epoch 5/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6270 - Precision: 0.5126 - Recall: 0.3637 - accuracy: 0.5213 - loss: 1.3227 Epoch 6/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6097 - Precision: 0.4673 - Recall: 0.1915 - accuracy: 0.5025 - loss: 1.0490 Epoch 7/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6103 - Precision: 0.5057 - Recall: 0.2868 - accuracy: 0.5064 - loss: 1.0973 Epoch 8/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6191 - Precision: 0.5161 - Recall: 0.2524 - accuracy: 0.4765 - loss: 1.0548 Epoch 9/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6123 - Precision: 0.4892 - Recall: 0.3447 - accuracy: 0.4892 - loss: 1.0585 Epoch 10/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5949 - Precision: 0.4564 - Recall: 0.1864 - accuracy: 0.4732 - loss: 3.2908 Epoch 11/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5959 - Precision: 0.4605 - Recall: 0.2168 - accuracy: 0.4843 - loss: 1.1373 Epoch 12/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6266 - Precision: 0.4454 - Recall: 0.2370 - accuracy: 0.4879 - loss: 1.0524 Epoch 13/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6003 - Precision: 0.4313 - Recall: 0.2289 - accuracy: 0.4792 - loss: 1.0656 Epoch 14/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5780 - Precision: 0.3900 - Recall: 0.1997 - accuracy: 0.4725 - loss: 1.0890 Epoch 15/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6229 - Precision: 0.4669 - Recall: 0.2588 - accuracy: 0.5103 - loss: 2.2652 Epoch 16/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5763 - Precision: 0.3887 - Recall: 0.1238 - accuracy: 0.4780 - loss: 1.0739 Epoch 17/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5856 - Precision: 0.3768 - Recall: 0.1340 - accuracy: 0.4792 - loss: 1.0717 Epoch 18/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6317 - Precision: 0.5265 - Recall: 0.3853 - accuracy: 0.5274 - loss: 1.0278 Epoch 19/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5777 - Precision: 0.4175 - Recall: 0.1603 - accuracy: 0.4664 - loss: 1.2794 Epoch 20/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6337 - Precision: 0.5175 - Recall: 0.3747 - accuracy: 0.5266 - loss: 1.0285 Epoch 21/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5389 - Precision: 0.3239 - Recall: 0.1127 - accuracy: 0.3748 - loss: 1.1003 Epoch 22/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6126 - Precision: 0.4505 - Recall: 0.2438 - accuracy: 0.5055 - loss: 1.0530 Epoch 23/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6099 - Precision: 0.4500 - Recall: 0.2065 - accuracy: 0.5075 - loss: 1.0509 Epoch 24/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6047 - Precision: 0.3666 - Recall: 0.1186 - accuracy: 0.5032 - loss: 1.0458 Epoch 25/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6080 - Precision: 0.3625 - Recall: 0.1003 - accuracy: 0.4697 - loss: 1.0674 Epoch 26/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6029 - Precision: 0.4734 - Recall: 0.2726 - accuracy: 0.5035 - loss: 1.0670 Epoch 27/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6149 - Precision: 0.4796 - Recall: 0.3349 - accuracy: 0.5075 - loss: 1.0464 Epoch 28/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6332 - Precision: 0.4856 - Recall: 0.2815 - accuracy: 0.5158 - loss: 1.0404 Epoch 29/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6410 - Precision: 0.4820 - Recall: 0.2074 - accuracy: 0.5071 - loss: 1.0434 Epoch 30/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6177 - Precision: 0.4639 - Recall: 0.2311 - accuracy: 0.5031 - loss: 1.0597 Epoch 31/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6125 - Precision: 0.4019 - Recall: 0.1632 - accuracy: 0.4780 - loss: 1.0605 Epoch 32/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6325 - Precision: 0.4150 - Recall: 0.1370 - accuracy: 0.4998 - loss: 1.0489 Epoch 33/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6411 - Precision: 0.5201 - Recall: 0.2365 - accuracy: 0.5122 - loss: 1.0375 Epoch 34/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5933 - Precision: 0.4571 - Recall: 0.2198 - accuracy: 0.4683 - loss: 1.0710 Epoch 35/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5957 - Precision: 0.2836 - Recall: 0.0868 - accuracy: 0.4576 - loss: 1.0733 Epoch 36/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6027 - Precision: 0.4728 - Recall: 0.2704 - accuracy: 0.4850 - loss: 1.0782 Epoch 37/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6023 - Precision: 0.4800 - Recall: 0.3859 - accuracy: 0.4922 - loss: 1.0615 Epoch 38/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6104 - Precision: 0.5056 - Recall: 0.2950 - accuracy: 0.5001 - loss: 1.0591 Epoch 39/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5647 - Precision: 0.3237 - Recall: 0.1304 - accuracy: 0.4228 - loss: 1.0892 Epoch 40/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6131 - Precision: 0.4171 - Recall: 0.1373 - accuracy: 0.4973 - loss: 1.0605 Epoch 41/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6275 - Precision: 0.4608 - Recall: 0.2102 - accuracy: 0.4997 - loss: 1.0508 Epoch 42/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6101 - Precision: 0.4167 - Recall: 0.1988 - accuracy: 0.4753 - loss: 1.0641 Epoch 43/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6066 - Precision: 0.3434 - Recall: 0.1050 - accuracy: 0.4843 - loss: 1.0622 Epoch 44/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6222 - Precision: 0.5233 - Recall: 0.3517 - accuracy: 0.5155 - loss: 1.0491 Epoch 45/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6033 - Precision: 0.4190 - Recall: 0.2259 - accuracy: 0.5096 - loss: 1.0717 Epoch 46/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5921 - Precision: 0.4446 - Recall: 0.1830 - accuracy: 0.4784 - loss: 1.0722 Epoch 47/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6364 - Precision: 0.5250 - Recall: 0.3634 - accuracy: 0.5399 - loss: 1.0260 Epoch 48/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5943 - Precision: 0.3629 - Recall: 0.1522 - accuracy: 0.4902 - loss: 1.0655 Epoch 49/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6039 - Precision: 0.3792 - Recall: 0.1544 - accuracy: 0.4817 - loss: 1.0599 Epoch 50/50 146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6279 - Precision: 0.4871 - Recall: 0.2693 - accuracy: 0.5215 - loss: 1.0457 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 36ms/step Epoch 1/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 6s 9ms/step - AUC: 0.5209 - Precision: 0.3670 - Recall: 0.3034 - accuracy: 0.3735 - loss: 14.7581 Epoch 2/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6170 - Precision: 0.4204 - Recall: 0.1277 - accuracy: 0.4946 - loss: 10.0535 Epoch 3/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6075 - Precision: 0.4413 - Recall: 0.1302 - accuracy: 0.4782 - loss: 1.6304 Epoch 4/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6065 - Precision: 0.4600 - Recall: 0.1402 - accuracy: 0.4796 - loss: 1.5227 Epoch 5/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.5765 - Precision: 0.4256 - Recall: 0.2525 - accuracy: 0.4691 - loss: 1.0879 Epoch 6/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6248 - Precision: 0.3983 - Recall: 0.1470 - accuracy: 0.4973 - loss: 1.0486 Epoch 7/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5887 - Precision: 0.2729 - Recall: 0.1053 - accuracy: 0.4843 - loss: 1.2315 Epoch 8/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5814 - Precision: 0.2848 - Recall: 0.0789 - accuracy: 0.4283 - loss: 1.0765 Epoch 9/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6073 - Precision: 0.5007 - Recall: 0.3154 - accuracy: 0.4920 - loss: 1.2648 Epoch 10/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6106 - Precision: 0.3942 - Recall: 0.0921 - accuracy: 0.4892 - loss: 1.0535 Epoch 11/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6197 - Precision: 0.4801 - Recall: 0.3172 - accuracy: 0.4928 - loss: 1.0597 Epoch 12/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6026 - Precision: 0.3265 - Recall: 0.0534 - accuracy: 0.4861 - loss: 1.0597 Epoch 13/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6200 - Precision: 0.5021 - Recall: 0.2251 - accuracy: 0.4894 - loss: 1.0570 Epoch 14/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6026 - Precision: 0.4411 - Recall: 0.1344 - accuracy: 0.4864 - loss: 1.0568 Epoch 15/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6104 - Precision: 0.4852 - Recall: 0.2774 - accuracy: 0.4937 - loss: 1.0618 Epoch 16/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.5957 - Precision: 0.4618 - Recall: 0.1980 - accuracy: 0.4922 - loss: 1.0586 Epoch 17/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6249 - Precision: 0.5149 - Recall: 0.3511 - accuracy: 0.5101 - loss: 1.0417 Epoch 18/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5929 - Precision: 0.3462 - Recall: 0.1368 - accuracy: 0.4768 - loss: 1.0664 Epoch 19/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6150 - Precision: 0.5046 - Recall: 0.3016 - accuracy: 0.4929 - loss: 1.0552 Epoch 20/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6450 - Precision: 0.4165 - Recall: 0.2004 - accuracy: 0.5243 - loss: 1.0383 Epoch 21/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5686 - Precision: 0.3498 - Recall: 0.1074 - accuracy: 0.4904 - loss: 1.0622 Epoch 22/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6176 - Precision: 0.5007 - Recall: 0.3288 - accuracy: 0.4965 - loss: 1.0498 Epoch 23/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5776 - Precision: 0.2727 - Recall: 0.0572 - accuracy: 0.4130 - loss: 1.0812 Epoch 24/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6171 - Precision: 0.4715 - Recall: 0.2577 - accuracy: 0.5006 - loss: 1.0600 Epoch 25/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6095 - Precision: 0.4312 - Recall: 0.2323 - accuracy: 0.4894 - loss: 1.0572 Epoch 26/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5829 - Precision: 0.4380 - Recall: 0.2723 - accuracy: 0.4865 - loss: 1.0621 Epoch 27/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6068 - Precision: 0.3124 - Recall: 0.0922 - accuracy: 0.4729 - loss: 1.0640 Epoch 28/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6070 - Precision: 0.4979 - Recall: 0.3212 - accuracy: 0.4964 - loss: 1.0507 Epoch 29/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6642 - Precision: 0.5171 - Recall: 0.3345 - accuracy: 0.5238 - loss: 1.0191 Epoch 30/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6193 - Precision: 0.3249 - Recall: 0.1011 - accuracy: 0.4846 - loss: 1.0600 Epoch 31/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6223 - Precision: 0.5287 - Recall: 0.4649 - accuracy: 0.5132 - loss: 1.0312 Epoch 32/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6276 - Precision: 0.5354 - Recall: 0.5043 - accuracy: 0.5298 - loss: 1.0321 Epoch 33/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6065 - Precision: 0.4083 - Recall: 0.1560 - accuracy: 0.4912 - loss: 1.0607 Epoch 34/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6210 - Precision: 0.4364 - Recall: 0.2144 - accuracy: 0.5072 - loss: 1.0554 Epoch 35/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6099 - Precision: 0.3593 - Recall: 0.1301 - accuracy: 0.4904 - loss: 1.0634 Epoch 36/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 14ms/step - AUC: 0.6198 - Precision: 0.3839 - Recall: 0.1780 - accuracy: 0.5063 - loss: 1.0415 Epoch 37/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6126 - Precision: 0.4415 - Recall: 0.2479 - accuracy: 0.5204 - loss: 1.0450 Epoch 38/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5898 - Precision: 0.4475 - Recall: 0.1543 - accuracy: 0.4691 - loss: 1.0765 Epoch 39/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5962 - Precision: 0.4228 - Recall: 0.1652 - accuracy: 0.4693 - loss: 1.0728 Epoch 40/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5943 - Precision: 0.4497 - Recall: 0.2788 - accuracy: 0.4852 - loss: 1.0762 Epoch 41/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6121 - Precision: 0.4913 - Recall: 0.3962 - accuracy: 0.4980 - loss: 1.0467 Epoch 42/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6220 - Precision: 0.4986 - Recall: 0.3641 - accuracy: 0.5002 - loss: 1.0444 Epoch 43/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6292 - Precision: 0.4121 - Recall: 0.1897 - accuracy: 0.5115 - loss: 1.0483 Epoch 44/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6264 - Precision: 0.4209 - Recall: 0.1859 - accuracy: 0.4937 - loss: 1.0515 Epoch 45/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6141 - Precision: 0.2687 - Recall: 0.0466 - accuracy: 0.5023 - loss: 1.0505 Epoch 46/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6261 - Precision: 0.4652 - Recall: 0.2485 - accuracy: 0.5332 - loss: 1.0319 Epoch 47/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6290 - Precision: 0.4252 - Recall: 0.1787 - accuracy: 0.5248 - loss: 1.0503 Epoch 48/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6233 - Precision: 0.3699 - Recall: 0.1286 - accuracy: 0.5025 - loss: 1.0441 Epoch 49/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6114 - Precision: 0.3457 - Recall: 0.0841 - accuracy: 0.4857 - loss: 1.0554 Epoch 50/50 73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5825 - Precision: 0.3684 - Recall: 0.1263 - accuracy: 0.4808 - loss: 1.0703 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 28ms/step Epoch 1/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 5s 10ms/step - AUC: 0.5413 - Precision: 0.3544 - Recall: 0.2835 - accuracy: 0.3578 - loss: 9.7574 Epoch 2/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6099 - Precision: 0.4815 - Recall: 0.4492 - accuracy: 0.4991 - loss: 7.8835 Epoch 3/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6016 - Precision: 0.3987 - Recall: 0.0381 - accuracy: 0.4885 - loss: 2.7958 Epoch 4/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6194 - Precision: 0.4462 - Recall: 0.1609 - accuracy: 0.4782 - loss: 1.4607 Epoch 5/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6248 - Precision: 0.5969 - Recall: 0.0745 - accuracy: 0.5208 - loss: 1.0485 Epoch 6/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6532 - Precision: 0.4508 - Recall: 0.2392 - accuracy: 0.5446 - loss: 1.2881 Epoch 7/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5902 - Precision: 0.1961 - Recall: 0.0559 - accuracy: 0.4643 - loss: 2.4603 Epoch 8/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6250 - Precision: 0.5156 - Recall: 0.4353 - accuracy: 0.5114 - loss: 1.0546 Epoch 9/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5988 - Precision: 0.9086 - Recall: 0.0196 - accuracy: 0.4897 - loss: 1.0465 Epoch 10/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6095 - Precision: 0.4895 - Recall: 0.3066 - accuracy: 0.4905 - loss: 1.0523 Epoch 11/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6269 - Precision: 0.5079 - Recall: 0.5008 - accuracy: 0.5059 - loss: 1.7394 Epoch 12/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6229 - Precision: 0.4293 - Recall: 0.1048 - accuracy: 0.5098 - loss: 1.2826 Epoch 13/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6180 - Precision: 0.3375 - Recall: 0.1469 - accuracy: 0.4948 - loss: 1.4560 Epoch 14/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6156 - Precision: 0.3640 - Recall: 0.1920 - accuracy: 0.4989 - loss: 1.0469 Epoch 15/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6120 - Precision: 0.3678 - Recall: 0.1630 - accuracy: 0.4916 - loss: 1.0575 Epoch 16/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6299 - Precision: 0.4736 - Recall: 0.2804 - accuracy: 0.5261 - loss: 1.0356 Epoch 17/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6625 - Precision: 0.4390 - Recall: 0.2664 - accuracy: 0.5408 - loss: 1.0173 Epoch 18/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5681 - Precision: 0.2918 - Recall: 0.1024 - accuracy: 0.4161 - loss: 1.0891 Epoch 19/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.5772 - Precision: 0.1928 - Recall: 0.0611 - accuracy: 0.4547 - loss: 1.0748 Epoch 20/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6213 - Precision: 0.4826 - Recall: 0.3029 - accuracy: 0.4851 - loss: 1.0546 Epoch 21/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6112 - Precision: 0.4884 - Recall: 0.3119 - accuracy: 0.4872 - loss: 1.0573 Epoch 22/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6122 - Precision: 0.5179 - Recall: 0.4929 - accuracy: 0.5170 - loss: 1.0379 Epoch 23/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6360 - Precision: 0.2666 - Recall: 0.0910 - accuracy: 0.4957 - loss: 1.0494 Epoch 24/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6145 - Precision: 0.3726 - Recall: 0.0736 - accuracy: 0.4887 - loss: 1.0858 Epoch 25/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5828 - Precision: 0.4556 - Recall: 0.3332 - accuracy: 0.4901 - loss: 1.0752 Epoch 26/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.6073 - Precision: 0.2440 - Recall: 0.0699 - accuracy: 0.4772 - loss: 1.0548 Epoch 27/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5856 - Precision: 0.4117 - Recall: 0.1572 - accuracy: 0.4682 - loss: 1.0698 Epoch 28/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6067 - Precision: 0.4802 - Recall: 0.3011 - accuracy: 0.4851 - loss: 1.1464 Epoch 29/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6361 - Precision: 0.5142 - Recall: 0.4249 - accuracy: 0.5149 - loss: 1.0310 Epoch 30/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5960 - Precision: 0.3700 - Recall: 0.1494 - accuracy: 0.4905 - loss: 1.0551 Epoch 31/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6016 - Precision: 0.4524 - Recall: 0.2198 - accuracy: 0.4888 - loss: 1.0517 Epoch 32/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5923 - Precision: 0.4488 - Recall: 0.2326 - accuracy: 0.4741 - loss: 1.0696 Epoch 33/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6175 - Precision: 0.5045 - Recall: 0.4374 - accuracy: 0.4997 - loss: 1.0528 Epoch 34/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5923 - Precision: 0.4868 - Recall: 0.3289 - accuracy: 0.4852 - loss: 1.0620 Epoch 35/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5895 - Precision: 0.4721 - Recall: 0.3585 - accuracy: 0.4732 - loss: 1.0757 Epoch 36/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.5837 - Precision: 0.4435 - Recall: 0.2931 - accuracy: 0.4796 - loss: 1.0686 Epoch 37/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.5798 - Precision: 0.4057 - Recall: 0.2008 - accuracy: 0.4880 - loss: 1.0574 Epoch 38/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5760 - Precision: 0.3245 - Recall: 0.1036 - accuracy: 0.4770 - loss: 1.0629 Epoch 39/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5723 - Precision: 0.4184 - Recall: 0.2136 - accuracy: 0.4659 - loss: 1.0706 Epoch 40/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6305 - Precision: 0.4772 - Recall: 0.3819 - accuracy: 0.4970 - loss: 1.0535 Epoch 41/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6117 - Precision: 0.1145 - Recall: 0.0137 - accuracy: 0.4868 - loss: 1.0550 Epoch 42/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6379 - Precision: 0.5075 - Recall: 0.3595 - accuracy: 0.5084 - loss: 1.0370 Epoch 43/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6319 - Precision: 0.4962 - Recall: 0.4152 - accuracy: 0.5192 - loss: 1.0293 Epoch 44/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6123 - Precision: 0.1807 - Recall: 0.0392 - accuracy: 0.4962 - loss: 1.0547 Epoch 45/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6410 - Precision: 0.5186 - Recall: 0.2680 - accuracy: 0.5232 - loss: 1.0243 Epoch 46/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5846 - Precision: 0.3252 - Recall: 0.1117 - accuracy: 0.4750 - loss: 1.0624 Epoch 47/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.6296 - Precision: 0.5420 - Recall: 0.4441 - accuracy: 0.5293 - loss: 1.0267 Epoch 48/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6467 - Precision: 0.4551 - Recall: 0.2686 - accuracy: 0.5248 - loss: 1.0330 Epoch 49/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6273 - Precision: 0.3508 - Recall: 0.1345 - accuracy: 0.5080 - loss: 1.0449 Epoch 50/50 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5964 - Precision: 0.1862 - Recall: 0.0445 - accuracy: 0.4857 - loss: 1.0588 5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 45ms/step Best hyperparameter combination: {'learning_rate': 0.001, 'dropout_rate': 0.4, 'batch_size': 16, 'accuracy': 0.7945205479452054, 'precision': 0.76454307568438, 'recall': 0.7729955229955231, 'f1': 0.7661143330571666}
Escogemos los mejores parámetros y entrenamos modelo
from keras.models import Sequential
from keras.layers import Dense, Dropout, BatchNormalization, Input
from keras.optimizers import Adam
from keras.callbacks import EarlyStopping
# Parámetros óptimos encontrados previamente
dropout_rate = 0.4
learning_rate = 0.001
batch_size = 16
input_dim = X_train_scaled.shape[1]
n_classes = Y_train_onehot.shape[1]
# Definición del modelo
best_model = Sequential([
Input(shape=(input_dim,)),
Dense(256, activation='relu'),
BatchNormalization(),
Dropout(dropout_rate),
Dense(128, activation='tanh'),
Dropout(dropout_rate),
Dense(64, activation='relu'),
Dropout(dropout_rate),
Dense(32, activation='relu'),
Dropout(dropout_rate),
Dense(16, activation='relu'),
Dense(n_classes, activation='softmax')
])
# Compilación del modelo
best_model.compile(
optimizer=Adam(learning_rate=learning_rate),
loss='categorical_crossentropy',
metrics=['accuracy', 'Precision', 'Recall']
)
# EarlyStopping para prevenir sobreajuste
early_stop = EarlyStopping(
monitor='val_loss',
patience=10,
restore_best_weights=True
)
# Entrenamiento con conjunto de validación
history = best_model.fit(
X_train_scaled,
Y_train_onehot,
validation_data=(X_test_scaled, Y_test_onehot),
epochs=100,
batch_size=batch_size,
callbacks=[early_stop],
verbose=1
)
Epoch 1/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 9s 36ms/step - Precision: 0.3090 - Recall: 0.1513 - accuracy: 0.3255 - loss: 1.2461 - val_Precision: 1.0000 - val_Recall: 0.1301 - val_accuracy: 0.5000 - val_loss: 0.9917 Epoch 2/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - Precision: 0.6243 - Recall: 0.3434 - accuracy: 0.5097 - loss: 0.9603 - val_Precision: 0.9189 - val_Recall: 0.2329 - val_accuracy: 0.6164 - val_loss: 0.8791 Epoch 3/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7623 - Recall: 0.4047 - accuracy: 0.6008 - loss: 0.8322 - val_Precision: 0.9333 - val_Recall: 0.2877 - val_accuracy: 0.6644 - val_loss: 0.8002 Epoch 4/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7303 - Recall: 0.4607 - accuracy: 0.6031 - loss: 0.7765 - val_Precision: 0.9362 - val_Recall: 0.3014 - val_accuracy: 0.6781 - val_loss: 0.7590 Epoch 5/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7834 - Recall: 0.4947 - accuracy: 0.6447 - loss: 0.7335 - val_Precision: 0.9333 - val_Recall: 0.3836 - val_accuracy: 0.6575 - val_loss: 0.7193 Epoch 6/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7288 - Recall: 0.5164 - accuracy: 0.6357 - loss: 0.7262 - val_Precision: 0.9242 - val_Recall: 0.4178 - val_accuracy: 0.6986 - val_loss: 0.6731 Epoch 7/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - Precision: 0.7559 - Recall: 0.5393 - accuracy: 0.6625 - loss: 0.6738 - val_Precision: 0.9048 - val_Recall: 0.5205 - val_accuracy: 0.7123 - val_loss: 0.6501 Epoch 8/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - Precision: 0.7255 - Recall: 0.5454 - accuracy: 0.6645 - loss: 0.6646 - val_Precision: 0.8876 - val_Recall: 0.5411 - val_accuracy: 0.7192 - val_loss: 0.6450 Epoch 9/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - Precision: 0.7548 - Recall: 0.5778 - accuracy: 0.6727 - loss: 0.6325 - val_Precision: 0.8778 - val_Recall: 0.5411 - val_accuracy: 0.7329 - val_loss: 0.6283 Epoch 10/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7450 - Recall: 0.5880 - accuracy: 0.6669 - loss: 0.6419 - val_Precision: 0.8750 - val_Recall: 0.5753 - val_accuracy: 0.6986 - val_loss: 0.6129 Epoch 11/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7963 - Recall: 0.5836 - accuracy: 0.7035 - loss: 0.5603 - val_Precision: 0.8252 - val_Recall: 0.5822 - val_accuracy: 0.7123 - val_loss: 0.6418 Epoch 12/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7687 - Recall: 0.5799 - accuracy: 0.6818 - loss: 0.6573 - val_Precision: 0.8100 - val_Recall: 0.5548 - val_accuracy: 0.7055 - val_loss: 0.5969 Epoch 13/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - Precision: 0.7607 - Recall: 0.5620 - accuracy: 0.6456 - loss: 0.6385 - val_Precision: 0.8526 - val_Recall: 0.5548 - val_accuracy: 0.7055 - val_loss: 0.5928 Epoch 14/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7671 - Recall: 0.5730 - accuracy: 0.6767 - loss: 0.6090 - val_Precision: 0.8556 - val_Recall: 0.5274 - val_accuracy: 0.6712 - val_loss: 0.5984 Epoch 15/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7944 - Recall: 0.5817 - accuracy: 0.7148 - loss: 0.5871 - val_Precision: 0.8396 - val_Recall: 0.6096 - val_accuracy: 0.6918 - val_loss: 0.5937 Epoch 16/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7809 - Recall: 0.5916 - accuracy: 0.7254 - loss: 0.5335 - val_Precision: 0.8333 - val_Recall: 0.5822 - val_accuracy: 0.7192 - val_loss: 0.5980 Epoch 17/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - Precision: 0.7549 - Recall: 0.5900 - accuracy: 0.6868 - loss: 0.5441 - val_Precision: 0.8515 - val_Recall: 0.5890 - val_accuracy: 0.7123 - val_loss: 0.6013 Epoch 18/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7668 - Recall: 0.6205 - accuracy: 0.6994 - loss: 0.5715 - val_Precision: 0.8286 - val_Recall: 0.5959 - val_accuracy: 0.7329 - val_loss: 0.5744 Epoch 19/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7712 - Recall: 0.6227 - accuracy: 0.7151 - loss: 0.5802 - val_Precision: 0.8469 - val_Recall: 0.5685 - val_accuracy: 0.7466 - val_loss: 0.5545 Epoch 20/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - Precision: 0.7903 - Recall: 0.6332 - accuracy: 0.7384 - loss: 0.5223 - val_Precision: 0.8103 - val_Recall: 0.6438 - val_accuracy: 0.7192 - val_loss: 0.5614 Epoch 21/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7695 - Recall: 0.6430 - accuracy: 0.7247 - loss: 0.5445 - val_Precision: 0.8158 - val_Recall: 0.6370 - val_accuracy: 0.7192 - val_loss: 0.5765 Epoch 22/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.8077 - Recall: 0.6579 - accuracy: 0.7455 - loss: 0.5471 - val_Precision: 0.8376 - val_Recall: 0.6712 - val_accuracy: 0.7466 - val_loss: 0.5733 Epoch 23/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7798 - Recall: 0.5976 - accuracy: 0.7417 - loss: 0.5521 - val_Precision: 0.8205 - val_Recall: 0.6575 - val_accuracy: 0.7603 - val_loss: 0.5444 Epoch 24/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7700 - Recall: 0.6365 - accuracy: 0.7360 - loss: 0.5463 - val_Precision: 0.8130 - val_Recall: 0.6849 - val_accuracy: 0.7603 - val_loss: 0.5416 Epoch 25/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7648 - Recall: 0.6518 - accuracy: 0.7348 - loss: 0.5170 - val_Precision: 0.8099 - val_Recall: 0.6712 - val_accuracy: 0.7260 - val_loss: 0.5479 Epoch 26/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - Precision: 0.8154 - Recall: 0.6836 - accuracy: 0.7654 - loss: 0.5129 - val_Precision: 0.8099 - val_Recall: 0.6712 - val_accuracy: 0.7534 - val_loss: 0.5322 Epoch 27/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7558 - Recall: 0.6452 - accuracy: 0.7207 - loss: 0.6175 - val_Precision: 0.7899 - val_Recall: 0.6438 - val_accuracy: 0.7192 - val_loss: 0.5485 Epoch 28/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7886 - Recall: 0.6844 - accuracy: 0.7354 - loss: 0.5267 - val_Precision: 0.8120 - val_Recall: 0.6507 - val_accuracy: 0.7192 - val_loss: 0.5491 Epoch 29/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7912 - Recall: 0.6528 - accuracy: 0.7352 - loss: 0.5322 - val_Precision: 0.8182 - val_Recall: 0.6781 - val_accuracy: 0.7397 - val_loss: 0.5505 Epoch 30/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7637 - Recall: 0.6767 - accuracy: 0.7276 - loss: 0.5324 - val_Precision: 0.8348 - val_Recall: 0.6575 - val_accuracy: 0.7192 - val_loss: 0.5536 Epoch 31/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7862 - Recall: 0.6683 - accuracy: 0.7575 - loss: 0.5211 - val_Precision: 0.8250 - val_Recall: 0.6781 - val_accuracy: 0.7534 - val_loss: 0.5293 Epoch 32/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.8271 - Recall: 0.6603 - accuracy: 0.7743 - loss: 0.4825 - val_Precision: 0.8293 - val_Recall: 0.6986 - val_accuracy: 0.7260 - val_loss: 0.5010 Epoch 33/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.8311 - Recall: 0.7402 - accuracy: 0.7918 - loss: 0.4672 - val_Precision: 0.7984 - val_Recall: 0.7055 - val_accuracy: 0.7534 - val_loss: 0.5079 Epoch 34/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.8175 - Recall: 0.7375 - accuracy: 0.7802 - loss: 0.4893 - val_Precision: 0.8254 - val_Recall: 0.7123 - val_accuracy: 0.7466 - val_loss: 0.5057 Epoch 35/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7860 - Recall: 0.7104 - accuracy: 0.7516 - loss: 0.4551 - val_Precision: 0.8217 - val_Recall: 0.7260 - val_accuracy: 0.7603 - val_loss: 0.5073 Epoch 36/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.8130 - Recall: 0.7220 - accuracy: 0.7731 - loss: 0.4699 - val_Precision: 0.7829 - val_Recall: 0.6918 - val_accuracy: 0.7260 - val_loss: 0.5549 Epoch 37/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.8065 - Recall: 0.6949 - accuracy: 0.7556 - loss: 0.4824 - val_Precision: 0.8387 - val_Recall: 0.7123 - val_accuracy: 0.7534 - val_loss: 0.5048 Epoch 38/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - Precision: 0.7831 - Recall: 0.6593 - accuracy: 0.7537 - loss: 0.4768 - val_Precision: 0.8293 - val_Recall: 0.6986 - val_accuracy: 0.7534 - val_loss: 0.4940 Epoch 39/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7850 - Recall: 0.6854 - accuracy: 0.7379 - loss: 0.5276 - val_Precision: 0.8189 - val_Recall: 0.7123 - val_accuracy: 0.7466 - val_loss: 0.5344 Epoch 40/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7801 - Recall: 0.6677 - accuracy: 0.7268 - loss: 0.5463 - val_Precision: 0.8115 - val_Recall: 0.6781 - val_accuracy: 0.7397 - val_loss: 0.4913 Epoch 41/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.8324 - Recall: 0.7336 - accuracy: 0.7985 - loss: 0.4623 - val_Precision: 0.7874 - val_Recall: 0.6849 - val_accuracy: 0.7192 - val_loss: 0.4901 Epoch 42/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.8040 - Recall: 0.7287 - accuracy: 0.7732 - loss: 0.4738 - val_Precision: 0.8333 - val_Recall: 0.6849 - val_accuracy: 0.7603 - val_loss: 0.4771 Epoch 43/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.8312 - Recall: 0.7533 - accuracy: 0.7882 - loss: 0.4285 - val_Precision: 0.8115 - val_Recall: 0.6781 - val_accuracy: 0.7534 - val_loss: 0.4820 Epoch 44/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7942 - Recall: 0.7099 - accuracy: 0.7634 - loss: 0.4811 - val_Precision: 0.7786 - val_Recall: 0.6986 - val_accuracy: 0.7055 - val_loss: 0.5135 Epoch 45/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - Precision: 0.7757 - Recall: 0.6941 - accuracy: 0.7504 - loss: 0.5041 - val_Precision: 0.7937 - val_Recall: 0.6849 - val_accuracy: 0.7397 - val_loss: 0.5132 Epoch 46/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.8215 - Recall: 0.7060 - accuracy: 0.7792 - loss: 0.4612 - val_Precision: 0.8160 - val_Recall: 0.6986 - val_accuracy: 0.7466 - val_loss: 0.5033 Epoch 47/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.8198 - Recall: 0.7226 - accuracy: 0.7915 - loss: 0.4389 - val_Precision: 0.7812 - val_Recall: 0.6849 - val_accuracy: 0.7329 - val_loss: 0.5236 Epoch 48/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7951 - Recall: 0.6979 - accuracy: 0.7569 - loss: 0.5131 - val_Precision: 0.8095 - val_Recall: 0.6986 - val_accuracy: 0.7534 - val_loss: 0.4927 Epoch 49/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.8178 - Recall: 0.7295 - accuracy: 0.7618 - loss: 0.4797 - val_Precision: 0.7674 - val_Recall: 0.6781 - val_accuracy: 0.7329 - val_loss: 0.5109 Epoch 50/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - Precision: 0.7824 - Recall: 0.7248 - accuracy: 0.7593 - loss: 0.4685 - val_Precision: 0.7710 - val_Recall: 0.6918 - val_accuracy: 0.7260 - val_loss: 0.5161 Epoch 51/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - Precision: 0.7876 - Recall: 0.7022 - accuracy: 0.7511 - loss: 0.4606 - val_Precision: 0.7769 - val_Recall: 0.6918 - val_accuracy: 0.7260 - val_loss: 0.4966 Epoch 52/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - Precision: 0.8367 - Recall: 0.7642 - accuracy: 0.8130 - loss: 0.4078 - val_Precision: 0.7630 - val_Recall: 0.7055 - val_accuracy: 0.7329 - val_loss: 0.5114
Predecimos para dicho modelo
from sklearn.metrics import classification_report, confusion_matrix, ConfusionMatrixDisplay
import numpy as np
import matplotlib.pyplot as plt
# Predicciones
y_test_pred_probs = best_model.predict(X_test_scaled)
y_test_pred_labels = np.argmax(y_test_pred_probs, axis=1)
y_test_true_labels = np.argmax(Y_test_onehot, axis=1)
# Reporte
print("Classification Report:")
print(classification_report(y_test_true_labels, y_test_pred_labels, digits=3))
# Matriz de confusión
class_names = ['Elephant', 'Rhino', 'Others']
cm = confusion_matrix(y_test_true_labels, y_test_pred_labels)
disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=class_names)
disp.plot(cmap='Blues')
plt.title("Confusion Matrix - Test Set")
plt.xlabel("Predicted label")
plt.ylabel("True label")
plt.grid(False)
plt.show()
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 52ms/step Classification Report: precision recall f1-score support 0 0.686 0.615 0.649 39 1 0.535 0.657 0.590 35 2 0.941 0.889 0.914 72 accuracy 0.760 146 macro avg 0.721 0.720 0.718 146 weighted avg 0.776 0.760 0.766 146
Visualizamos predicciones en el test
import matplotlib.pyplot as plt
import numpy as np
# Número de ejemplos a mostrar
num_examples = 10
indices = np.random.choice(len(X_test_scaled), num_examples, replace=False)
# Nombres de clases
class_names = ['Elephant', 'Rhino', 'Others']
plt.figure(figsize=(12, 6 * num_examples // 3))
for i, idx in enumerate(indices):
img = imgs_test[idx]
mask = masks_test[idx]
true_label = y_test[idx]
pred_label = y_test_pred_labels[idx]
color = 'green' if true_label == pred_label else 'red'
# Imagen original
plt.subplot(num_examples, 2, 2 * i + 1)
plt.imshow(img)
plt.axis('off')
plt.title(f"[IMG] Real: {class_names[true_label]} | Pred: {class_names[pred_label]}", color=color)
# Máscara binaria
plt.subplot(num_examples, 2, 2 * i + 2)
plt.imshow(mask, cmap='gray')
plt.axis('off')
plt.title(f"[MASK] Figura binaria", color=color)
plt.suptitle("Predicciones del modelo con forma (máscara) incluida", fontsize=18)
plt.tight_layout()
plt.show()
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers). Got range [-0.11641828..1.0890203].
Ahora, para ver si hay diferencias, entrenamos el modelo solo con los canales RGB y el contorno
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from tensorflow.keras.utils import to_categorical
# Solo RGB figura (3), RGB fondo (3), contorno área (1) = 7 características
X_rgb_contour = X[:, :7]
X_train_rc, X_test_rc, y_train_rc, y_test_rc, imgs_train_rc, imgs_test_rc, masks_train_rc, masks_test_rc = train_test_split(
X_rgb_contour, etiquetas_aug, imagenes_aug, mascaras_aug, test_size=0.2, random_state=42
)
# Escalado
scaler_rc = StandardScaler()
X_train_rc_scaled = scaler_rc.fit_transform(X_train_rc)
X_test_rc_scaled = scaler_rc.transform(X_test_rc)
# One-hot encoding
y_train_rc = y_train_rc.astype("int32")
y_test_rc = y_test_rc.astype("int32")
Y_train_rc_onehot = to_categorical(y_train_rc, num_classes=4).astype("float32")
Y_test_rc_onehot = to_categorical(y_test_rc, num_classes=4).astype("float32")
from keras.models import Sequential
from keras.layers import Dense, Dropout, BatchNormalization, Input
from keras.optimizers import Adam
model_rgb_contour = Sequential([
Input(shape=(7,)), # Solo 7 características ahora
Dense(256, activation='relu'),
BatchNormalization(),
Dropout(0.4),
Dense(128, activation='tanh'),
Dropout(0.4),
Dense(64, activation='relu'),
Dropout(0.4),
Dense(32, activation='relu'),
Dropout(0.4),
Dense(16, activation='relu'),
Dense(4, activation='softmax')
])
model_rgb_contour.compile(
optimizer=Adam(learning_rate=0.001),
loss='categorical_crossentropy',
metrics=['accuracy', 'Precision', 'Recall', 'AUC']
)
history_rc = model_rgb_contour.fit(
X_train_rc_scaled,
Y_train_rc_onehot,
validation_data=(X_test_rc_scaled, Y_test_rc_onehot),
epochs=100,
batch_size=16,
verbose=1
)
Epoch 1/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 9s 38ms/step - AUC: 0.5404 - Precision: 0.3289 - Recall: 0.1348 - accuracy: 0.3484 - loss: 1.6884 - val_AUC: 0.9020 - val_Precision: 1.0000 - val_Recall: 0.0274 - val_accuracy: 0.6575 - val_loss: 1.1638 Epoch 2/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 1s 15ms/step - AUC: 0.8334 - Precision: 0.7109 - Recall: 0.3905 - accuracy: 0.6038 - loss: 0.9896 - val_AUC: 0.9293 - val_Precision: 1.0000 - val_Recall: 0.2877 - val_accuracy: 0.6575 - val_loss: 0.9294 Epoch 3/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.8618 - Precision: 0.6718 - Recall: 0.4973 - accuracy: 0.6103 - loss: 0.8734 - val_AUC: 0.9346 - val_Precision: 1.0000 - val_Recall: 0.4041 - val_accuracy: 0.6986 - val_loss: 0.7918 Epoch 4/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8711 - Precision: 0.6632 - Recall: 0.4816 - accuracy: 0.5918 - loss: 0.8621 - val_AUC: 0.9332 - val_Precision: 1.0000 - val_Recall: 0.4521 - val_accuracy: 0.7055 - val_loss: 0.7054 Epoch 5/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8980 - Precision: 0.7278 - Recall: 0.5781 - accuracy: 0.6735 - loss: 0.7737 - val_AUC: 0.9417 - val_Precision: 1.0000 - val_Recall: 0.4726 - val_accuracy: 0.7534 - val_loss: 0.6505 Epoch 6/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8816 - Precision: 0.6800 - Recall: 0.5264 - accuracy: 0.6129 - loss: 0.8142 - val_AUC: 0.9389 - val_Precision: 0.9733 - val_Recall: 0.5000 - val_accuracy: 0.7260 - val_loss: 0.6261 Epoch 7/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9120 - Precision: 0.7436 - Recall: 0.5613 - accuracy: 0.6789 - loss: 0.6863 - val_AUC: 0.9347 - val_Precision: 0.8690 - val_Recall: 0.5000 - val_accuracy: 0.6918 - val_loss: 0.5991 Epoch 8/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9044 - Precision: 0.7393 - Recall: 0.5729 - accuracy: 0.6890 - loss: 0.7368 - val_AUC: 0.9376 - val_Precision: 0.8706 - val_Recall: 0.5068 - val_accuracy: 0.7329 - val_loss: 0.5891 Epoch 9/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9052 - Precision: 0.6993 - Recall: 0.5429 - accuracy: 0.6603 - loss: 0.7014 - val_AUC: 0.9316 - val_Precision: 0.8706 - val_Recall: 0.5068 - val_accuracy: 0.7260 - val_loss: 0.5872 Epoch 10/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9093 - Precision: 0.7196 - Recall: 0.5509 - accuracy: 0.6591 - loss: 0.6864 - val_AUC: 0.9399 - val_Precision: 0.8421 - val_Recall: 0.5479 - val_accuracy: 0.7603 - val_loss: 0.5499 Epoch 11/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9283 - Precision: 0.7455 - Recall: 0.5950 - accuracy: 0.7090 - loss: 0.6190 - val_AUC: 0.9327 - val_Precision: 0.7265 - val_Recall: 0.5822 - val_accuracy: 0.6986 - val_loss: 0.5686 Epoch 12/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9218 - Precision: 0.7593 - Recall: 0.5778 - accuracy: 0.6882 - loss: 0.6337 - val_AUC: 0.9339 - val_Precision: 0.7864 - val_Recall: 0.5548 - val_accuracy: 0.7192 - val_loss: 0.5728 Epoch 13/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8965 - Precision: 0.6967 - Recall: 0.5145 - accuracy: 0.6267 - loss: 0.7293 - val_AUC: 0.9429 - val_Precision: 0.8155 - val_Recall: 0.5753 - val_accuracy: 0.7534 - val_loss: 0.5455 Epoch 14/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9101 - Precision: 0.7378 - Recall: 0.5630 - accuracy: 0.6755 - loss: 0.6729 - val_AUC: 0.9398 - val_Precision: 0.8095 - val_Recall: 0.5822 - val_accuracy: 0.7397 - val_loss: 0.5334 Epoch 15/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9150 - Precision: 0.7746 - Recall: 0.5984 - accuracy: 0.6779 - loss: 0.6765 - val_AUC: 0.9381 - val_Precision: 0.8333 - val_Recall: 0.5479 - val_accuracy: 0.7260 - val_loss: 0.5495 Epoch 16/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9167 - Precision: 0.7361 - Recall: 0.5619 - accuracy: 0.6546 - loss: 0.6513 - val_AUC: 0.9286 - val_Precision: 0.7131 - val_Recall: 0.5959 - val_accuracy: 0.6849 - val_loss: 0.5835 Epoch 17/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9161 - Precision: 0.7456 - Recall: 0.5804 - accuracy: 0.6757 - loss: 0.6728 - val_AUC: 0.9414 - val_Precision: 0.8208 - val_Recall: 0.5959 - val_accuracy: 0.7123 - val_loss: 0.5442 Epoch 18/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9201 - Precision: 0.7585 - Recall: 0.5618 - accuracy: 0.7011 - loss: 0.6376 - val_AUC: 0.9441 - val_Precision: 0.8018 - val_Recall: 0.6096 - val_accuracy: 0.7329 - val_loss: 0.5310 Epoch 19/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9278 - Precision: 0.7615 - Recall: 0.5962 - accuracy: 0.7011 - loss: 0.6158 - val_AUC: 0.9453 - val_Precision: 0.7931 - val_Recall: 0.6301 - val_accuracy: 0.7260 - val_loss: 0.5243 Epoch 20/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 1s 13ms/step - AUC: 0.9262 - Precision: 0.7403 - Recall: 0.5869 - accuracy: 0.6874 - loss: 0.6196 - val_AUC: 0.9366 - val_Precision: 0.7373 - val_Recall: 0.5959 - val_accuracy: 0.7260 - val_loss: 0.5433 Epoch 21/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9236 - Precision: 0.7545 - Recall: 0.5970 - accuracy: 0.6838 - loss: 0.6242 - val_AUC: 0.9484 - val_Precision: 0.7833 - val_Recall: 0.6438 - val_accuracy: 0.7466 - val_loss: 0.5177 Epoch 22/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9325 - Precision: 0.7962 - Recall: 0.6507 - accuracy: 0.7052 - loss: 0.5894 - val_AUC: 0.9416 - val_Precision: 0.7672 - val_Recall: 0.6096 - val_accuracy: 0.7603 - val_loss: 0.5345 Epoch 23/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9432 - Precision: 0.7956 - Recall: 0.6611 - accuracy: 0.7446 - loss: 0.5452 - val_AUC: 0.9404 - val_Precision: 0.7845 - val_Recall: 0.6233 - val_accuracy: 0.7329 - val_loss: 0.5474 Epoch 24/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 1s 12ms/step - AUC: 0.9387 - Precision: 0.7907 - Recall: 0.6673 - accuracy: 0.7322 - loss: 0.5679 - val_AUC: 0.9418 - val_Precision: 0.7583 - val_Recall: 0.6233 - val_accuracy: 0.7260 - val_loss: 0.5404 Epoch 25/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9371 - Precision: 0.7892 - Recall: 0.6608 - accuracy: 0.7284 - loss: 0.5698 - val_AUC: 0.9476 - val_Precision: 0.8198 - val_Recall: 0.6233 - val_accuracy: 0.7808 - val_loss: 0.5204 Epoch 26/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9271 - Precision: 0.7664 - Recall: 0.6193 - accuracy: 0.7083 - loss: 0.6010 - val_AUC: 0.9485 - val_Precision: 0.8246 - val_Recall: 0.6438 - val_accuracy: 0.7466 - val_loss: 0.5184 Epoch 27/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 11ms/step - AUC: 0.9183 - Precision: 0.7467 - Recall: 0.6055 - accuracy: 0.6898 - loss: 0.6563 - val_AUC: 0.9469 - val_Precision: 0.8190 - val_Recall: 0.6507 - val_accuracy: 0.7534 - val_loss: 0.5260 Epoch 28/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9409 - Precision: 0.8014 - Recall: 0.6552 - accuracy: 0.7260 - loss: 0.5631 - val_AUC: 0.9523 - val_Precision: 0.8017 - val_Recall: 0.6644 - val_accuracy: 0.7740 - val_loss: 0.4996 Epoch 29/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9295 - Precision: 0.7447 - Recall: 0.6125 - accuracy: 0.6815 - loss: 0.5989 - val_AUC: 0.9447 - val_Precision: 0.7984 - val_Recall: 0.6781 - val_accuracy: 0.7603 - val_loss: 0.5157 Epoch 30/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9401 - Precision: 0.7830 - Recall: 0.6795 - accuracy: 0.7411 - loss: 0.5648 - val_AUC: 0.9515 - val_Precision: 0.7881 - val_Recall: 0.6370 - val_accuracy: 0.7671 - val_loss: 0.5006 Epoch 31/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9290 - Precision: 0.7714 - Recall: 0.6222 - accuracy: 0.7224 - loss: 0.6152 - val_AUC: 0.9519 - val_Precision: 0.8190 - val_Recall: 0.6507 - val_accuracy: 0.7603 - val_loss: 0.5089 Epoch 32/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9273 - Precision: 0.7530 - Recall: 0.6045 - accuracy: 0.6838 - loss: 0.6186 - val_AUC: 0.9523 - val_Precision: 0.8160 - val_Recall: 0.6986 - val_accuracy: 0.8014 - val_loss: 0.5004 Epoch 33/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 1s 13ms/step - AUC: 0.9449 - Precision: 0.7995 - Recall: 0.6689 - accuracy: 0.7421 - loss: 0.5536 - val_AUC: 0.9490 - val_Precision: 0.8000 - val_Recall: 0.6849 - val_accuracy: 0.7808 - val_loss: 0.5285 Epoch 34/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 11ms/step - AUC: 0.9516 - Precision: 0.8225 - Recall: 0.7239 - accuracy: 0.7787 - loss: 0.5069 - val_AUC: 0.9485 - val_Precision: 0.7795 - val_Recall: 0.6781 - val_accuracy: 0.7329 - val_loss: 0.5131 Epoch 35/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9395 - Precision: 0.7909 - Recall: 0.6913 - accuracy: 0.7470 - loss: 0.5671 - val_AUC: 0.9471 - val_Precision: 0.8017 - val_Recall: 0.6644 - val_accuracy: 0.7397 - val_loss: 0.5216 Epoch 36/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9405 - Precision: 0.7744 - Recall: 0.6629 - accuracy: 0.7166 - loss: 0.5603 - val_AUC: 0.9518 - val_Precision: 0.8000 - val_Recall: 0.6849 - val_accuracy: 0.7740 - val_loss: 0.5058 Epoch 37/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9382 - Precision: 0.7628 - Recall: 0.6651 - accuracy: 0.7166 - loss: 0.5661 - val_AUC: 0.9497 - val_Precision: 0.8033 - val_Recall: 0.6712 - val_accuracy: 0.7671 - val_loss: 0.5242 Epoch 38/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9379 - Precision: 0.7842 - Recall: 0.6390 - accuracy: 0.7256 - loss: 0.5701 - val_AUC: 0.9493 - val_Precision: 0.8049 - val_Recall: 0.6781 - val_accuracy: 0.7808 - val_loss: 0.5234 Epoch 39/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9455 - Precision: 0.8162 - Recall: 0.6993 - accuracy: 0.7683 - loss: 0.5497 - val_AUC: 0.9510 - val_Precision: 0.7923 - val_Recall: 0.7055 - val_accuracy: 0.7740 - val_loss: 0.5185 Epoch 40/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9362 - Precision: 0.7584 - Recall: 0.6611 - accuracy: 0.7142 - loss: 0.5793 - val_AUC: 0.9538 - val_Precision: 0.8203 - val_Recall: 0.7192 - val_accuracy: 0.7877 - val_loss: 0.5023 Epoch 41/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9362 - Precision: 0.7873 - Recall: 0.6642 - accuracy: 0.7399 - loss: 0.6026 - val_AUC: 0.9506 - val_Precision: 0.8017 - val_Recall: 0.6644 - val_accuracy: 0.7671 - val_loss: 0.5059 Epoch 42/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9343 - Precision: 0.7748 - Recall: 0.6597 - accuracy: 0.7454 - loss: 0.5801 - val_AUC: 0.9433 - val_Precision: 0.7698 - val_Recall: 0.6644 - val_accuracy: 0.7534 - val_loss: 0.5334 Epoch 43/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9378 - Precision: 0.8204 - Recall: 0.6776 - accuracy: 0.7541 - loss: 0.5988 - val_AUC: 0.9539 - val_Precision: 0.8115 - val_Recall: 0.6781 - val_accuracy: 0.7945 - val_loss: 0.5157 Epoch 44/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 11ms/step - AUC: 0.9329 - Precision: 0.7994 - Recall: 0.6779 - accuracy: 0.7294 - loss: 0.6069 - val_AUC: 0.9435 - val_Precision: 0.7712 - val_Recall: 0.6233 - val_accuracy: 0.7466 - val_loss: 0.5460 Epoch 45/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9403 - Precision: 0.7765 - Recall: 0.6652 - accuracy: 0.7211 - loss: 0.5692 - val_AUC: 0.9601 - val_Precision: 0.8417 - val_Recall: 0.6918 - val_accuracy: 0.7808 - val_loss: 0.4804 Epoch 46/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9400 - Precision: 0.7749 - Recall: 0.6768 - accuracy: 0.7355 - loss: 0.5689 - val_AUC: 0.9591 - val_Precision: 0.8636 - val_Recall: 0.6507 - val_accuracy: 0.8219 - val_loss: 0.4860 Epoch 47/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9238 - Precision: 0.7375 - Recall: 0.6453 - accuracy: 0.7094 - loss: 0.6422 - val_AUC: 0.9558 - val_Precision: 0.8649 - val_Recall: 0.6575 - val_accuracy: 0.7945 - val_loss: 0.4848 Epoch 48/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9369 - Precision: 0.7983 - Recall: 0.6476 - accuracy: 0.7473 - loss: 0.5790 - val_AUC: 0.9537 - val_Precision: 0.8197 - val_Recall: 0.6849 - val_accuracy: 0.8082 - val_loss: 0.4971 Epoch 49/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9424 - Precision: 0.7630 - Recall: 0.6614 - accuracy: 0.7445 - loss: 0.5475 - val_AUC: 0.9547 - val_Precision: 0.8264 - val_Recall: 0.6849 - val_accuracy: 0.8014 - val_loss: 0.5012 Epoch 50/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9345 - Precision: 0.7397 - Recall: 0.6646 - accuracy: 0.7178 - loss: 0.5751 - val_AUC: 0.9580 - val_Precision: 0.8320 - val_Recall: 0.7123 - val_accuracy: 0.8151 - val_loss: 0.4876 Epoch 51/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9398 - Precision: 0.7817 - Recall: 0.6735 - accuracy: 0.7399 - loss: 0.5703 - val_AUC: 0.9549 - val_Precision: 0.8217 - val_Recall: 0.7260 - val_accuracy: 0.8151 - val_loss: 0.4997 Epoch 52/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9466 - Precision: 0.8011 - Recall: 0.7116 - accuracy: 0.7580 - loss: 0.5277 - val_AUC: 0.9578 - val_Precision: 0.8333 - val_Recall: 0.6849 - val_accuracy: 0.8014 - val_loss: 0.4903 Epoch 53/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9286 - Precision: 0.7357 - Recall: 0.6328 - accuracy: 0.7047 - loss: 0.6131 - val_AUC: 0.9603 - val_Precision: 0.8500 - val_Recall: 0.6986 - val_accuracy: 0.8151 - val_loss: 0.4798 Epoch 54/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9344 - Precision: 0.7560 - Recall: 0.6392 - accuracy: 0.7181 - loss: 0.5731 - val_AUC: 0.9603 - val_Precision: 0.8417 - val_Recall: 0.6918 - val_accuracy: 0.8082 - val_loss: 0.4812 Epoch 55/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9281 - Precision: 0.7613 - Recall: 0.6580 - accuracy: 0.7161 - loss: 0.6292 - val_AUC: 0.9618 - val_Precision: 0.8607 - val_Recall: 0.7192 - val_accuracy: 0.8082 - val_loss: 0.4737 Epoch 56/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9519 - Precision: 0.7998 - Recall: 0.6917 - accuracy: 0.7576 - loss: 0.4941 - val_AUC: 0.9563 - val_Precision: 0.8160 - val_Recall: 0.6986 - val_accuracy: 0.7808 - val_loss: 0.4883 Epoch 57/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9398 - Precision: 0.7747 - Recall: 0.6798 - accuracy: 0.7255 - loss: 0.5560 - val_AUC: 0.9616 - val_Precision: 0.8400 - val_Recall: 0.7192 - val_accuracy: 0.8082 - val_loss: 0.4687 Epoch 58/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9446 - Precision: 0.7764 - Recall: 0.6791 - accuracy: 0.7385 - loss: 0.5325 - val_AUC: 0.9623 - val_Precision: 0.8189 - val_Recall: 0.7123 - val_accuracy: 0.8014 - val_loss: 0.4643 Epoch 59/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9453 - Precision: 0.8092 - Recall: 0.7043 - accuracy: 0.7634 - loss: 0.5364 - val_AUC: 0.9631 - val_Precision: 0.8374 - val_Recall: 0.7055 - val_accuracy: 0.8151 - val_loss: 0.4629 Epoch 60/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9479 - Precision: 0.8096 - Recall: 0.6999 - accuracy: 0.7577 - loss: 0.5270 - val_AUC: 0.9612 - val_Precision: 0.8548 - val_Recall: 0.7260 - val_accuracy: 0.8425 - val_loss: 0.4776 Epoch 61/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9608 - Precision: 0.8177 - Recall: 0.7333 - accuracy: 0.7912 - loss: 0.4544 - val_AUC: 0.9640 - val_Precision: 0.8450 - val_Recall: 0.7466 - val_accuracy: 0.8219 - val_loss: 0.4543 Epoch 62/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 12ms/step - AUC: 0.9350 - Precision: 0.7699 - Recall: 0.6774 - accuracy: 0.7093 - loss: 0.5891 - val_AUC: 0.9656 - val_Precision: 0.8770 - val_Recall: 0.7329 - val_accuracy: 0.8356 - val_loss: 0.4557 Epoch 63/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9497 - Precision: 0.7887 - Recall: 0.6904 - accuracy: 0.7540 - loss: 0.5042 - val_AUC: 0.9674 - val_Precision: 0.8548 - val_Recall: 0.7260 - val_accuracy: 0.8151 - val_loss: 0.4488 Epoch 64/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9539 - Precision: 0.8047 - Recall: 0.7089 - accuracy: 0.7584 - loss: 0.4822 - val_AUC: 0.9595 - val_Precision: 0.8168 - val_Recall: 0.7329 - val_accuracy: 0.7945 - val_loss: 0.4657 Epoch 65/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9446 - Precision: 0.7922 - Recall: 0.6803 - accuracy: 0.7394 - loss: 0.5371 - val_AUC: 0.9655 - val_Precision: 0.8496 - val_Recall: 0.7740 - val_accuracy: 0.8288 - val_loss: 0.4424 Epoch 66/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9432 - Precision: 0.7950 - Recall: 0.6832 - accuracy: 0.7527 - loss: 0.5508 - val_AUC: 0.9627 - val_Precision: 0.8583 - val_Recall: 0.7466 - val_accuracy: 0.8356 - val_loss: 0.4711 Epoch 67/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9457 - Precision: 0.7706 - Recall: 0.6735 - accuracy: 0.7494 - loss: 0.5255 - val_AUC: 0.9677 - val_Precision: 0.8710 - val_Recall: 0.7397 - val_accuracy: 0.8356 - val_loss: 0.4450 Epoch 68/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9562 - Precision: 0.8160 - Recall: 0.7086 - accuracy: 0.7867 - loss: 0.4877 - val_AUC: 0.9672 - val_Precision: 0.8682 - val_Recall: 0.7671 - val_accuracy: 0.8219 - val_loss: 0.4525 Epoch 69/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9548 - Precision: 0.8274 - Recall: 0.7286 - accuracy: 0.7904 - loss: 0.4950 - val_AUC: 0.9648 - val_Precision: 0.8730 - val_Recall: 0.7534 - val_accuracy: 0.8356 - val_loss: 0.4622 Epoch 70/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9557 - Precision: 0.8247 - Recall: 0.6965 - accuracy: 0.7859 - loss: 0.4921 - val_AUC: 0.9656 - val_Precision: 0.8561 - val_Recall: 0.7740 - val_accuracy: 0.8219 - val_loss: 0.4453 Epoch 71/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9553 - Precision: 0.8118 - Recall: 0.7229 - accuracy: 0.7860 - loss: 0.4852 - val_AUC: 0.9669 - val_Precision: 0.8702 - val_Recall: 0.7808 - val_accuracy: 0.8493 - val_loss: 0.4431 Epoch 72/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 11ms/step - AUC: 0.9621 - Precision: 0.8357 - Recall: 0.7441 - accuracy: 0.7922 - loss: 0.4469 - val_AUC: 0.9675 - val_Precision: 0.8593 - val_Recall: 0.7945 - val_accuracy: 0.8288 - val_loss: 0.4312 Epoch 73/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9539 - Precision: 0.7920 - Recall: 0.7056 - accuracy: 0.7597 - loss: 0.4918 - val_AUC: 0.9567 - val_Precision: 0.8160 - val_Recall: 0.6986 - val_accuracy: 0.8082 - val_loss: 0.4683 Epoch 74/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9497 - Precision: 0.7675 - Recall: 0.7080 - accuracy: 0.7455 - loss: 0.4972 - val_AUC: 0.9693 - val_Precision: 0.8769 - val_Recall: 0.7808 - val_accuracy: 0.8356 - val_loss: 0.4432 Epoch 75/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9567 - Precision: 0.8156 - Recall: 0.7385 - accuracy: 0.7776 - loss: 0.4755 - val_AUC: 0.9685 - val_Precision: 0.8769 - val_Recall: 0.7808 - val_accuracy: 0.8630 - val_loss: 0.4354 Epoch 76/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9616 - Precision: 0.8241 - Recall: 0.7537 - accuracy: 0.7940 - loss: 0.4523 - val_AUC: 0.9659 - val_Precision: 0.8643 - val_Recall: 0.8288 - val_accuracy: 0.8630 - val_loss: 0.4444 Epoch 77/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9502 - Precision: 0.8209 - Recall: 0.7376 - accuracy: 0.7901 - loss: 0.5363 - val_AUC: 0.9701 - val_Precision: 0.8712 - val_Recall: 0.7877 - val_accuracy: 0.8630 - val_loss: 0.4359 Epoch 78/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9578 - Precision: 0.8338 - Recall: 0.7351 - accuracy: 0.7772 - loss: 0.4655 - val_AUC: 0.9704 - val_Precision: 0.8741 - val_Recall: 0.8082 - val_accuracy: 0.8493 - val_loss: 0.4189 Epoch 79/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9538 - Precision: 0.8207 - Recall: 0.7405 - accuracy: 0.7826 - loss: 0.5001 - val_AUC: 0.9660 - val_Precision: 0.8519 - val_Recall: 0.7877 - val_accuracy: 0.8288 - val_loss: 0.4490 Epoch 80/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9553 - Precision: 0.8077 - Recall: 0.7247 - accuracy: 0.7671 - loss: 0.4771 - val_AUC: 0.9641 - val_Precision: 0.8633 - val_Recall: 0.8219 - val_accuracy: 0.8562 - val_loss: 0.4581 Epoch 81/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9599 - Precision: 0.8331 - Recall: 0.7791 - accuracy: 0.8206 - loss: 0.4606 - val_AUC: 0.9721 - val_Precision: 0.8971 - val_Recall: 0.8356 - val_accuracy: 0.8767 - val_loss: 0.4118 Epoch 82/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9477 - Precision: 0.7712 - Recall: 0.7068 - accuracy: 0.7385 - loss: 0.5237 - val_AUC: 0.9734 - val_Precision: 0.9051 - val_Recall: 0.8493 - val_accuracy: 0.8904 - val_loss: 0.4075 Epoch 83/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9576 - Precision: 0.8260 - Recall: 0.7454 - accuracy: 0.7901 - loss: 0.4705 - val_AUC: 0.9727 - val_Precision: 0.9000 - val_Recall: 0.8630 - val_accuracy: 0.8836 - val_loss: 0.4261 Epoch 84/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9534 - Precision: 0.8057 - Recall: 0.7216 - accuracy: 0.7653 - loss: 0.4835 - val_AUC: 0.9747 - val_Precision: 0.8986 - val_Recall: 0.8493 - val_accuracy: 0.8767 - val_loss: 0.4055 Epoch 85/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9529 - Precision: 0.7889 - Recall: 0.7285 - accuracy: 0.7715 - loss: 0.4951 - val_AUC: 0.9701 - val_Precision: 0.8615 - val_Recall: 0.7671 - val_accuracy: 0.8493 - val_loss: 0.4238 Epoch 86/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9498 - Precision: 0.8152 - Recall: 0.7270 - accuracy: 0.7807 - loss: 0.5498 - val_AUC: 0.9771 - val_Precision: 0.9015 - val_Recall: 0.8151 - val_accuracy: 0.8630 - val_loss: 0.3960 Epoch 87/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9548 - Precision: 0.8271 - Recall: 0.7244 - accuracy: 0.7717 - loss: 0.5021 - val_AUC: 0.9760 - val_Precision: 0.8955 - val_Recall: 0.8219 - val_accuracy: 0.8699 - val_loss: 0.3971 Epoch 88/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9551 - Precision: 0.8255 - Recall: 0.7307 - accuracy: 0.8013 - loss: 0.4938 - val_AUC: 0.9778 - val_Precision: 0.9030 - val_Recall: 0.8288 - val_accuracy: 0.8836 - val_loss: 0.3855 Epoch 89/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9546 - Precision: 0.8282 - Recall: 0.7364 - accuracy: 0.7980 - loss: 0.5010 - val_AUC: 0.9741 - val_Precision: 0.9058 - val_Recall: 0.8562 - val_accuracy: 0.8699 - val_loss: 0.3917 Epoch 90/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9396 - Precision: 0.7844 - Recall: 0.6962 - accuracy: 0.7463 - loss: 0.5790 - val_AUC: 0.9770 - val_Precision: 0.8931 - val_Recall: 0.8014 - val_accuracy: 0.8767 - val_loss: 0.3964 Epoch 91/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9530 - Precision: 0.8127 - Recall: 0.7302 - accuracy: 0.7812 - loss: 0.5080 - val_AUC: 0.9701 - val_Precision: 0.8759 - val_Recall: 0.8219 - val_accuracy: 0.8630 - val_loss: 0.4166 Epoch 92/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9597 - Precision: 0.8362 - Recall: 0.7582 - accuracy: 0.8033 - loss: 0.4707 - val_AUC: 0.9743 - val_Precision: 0.8626 - val_Recall: 0.7740 - val_accuracy: 0.8493 - val_loss: 0.4056 Epoch 93/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9615 - Precision: 0.8208 - Recall: 0.7229 - accuracy: 0.7995 - loss: 0.4439 - val_AUC: 0.9746 - val_Precision: 0.8855 - val_Recall: 0.7945 - val_accuracy: 0.8562 - val_loss: 0.4144 Epoch 94/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9584 - Precision: 0.8372 - Recall: 0.7267 - accuracy: 0.7896 - loss: 0.4785 - val_AUC: 0.9739 - val_Precision: 0.8872 - val_Recall: 0.8082 - val_accuracy: 0.8699 - val_loss: 0.4048 Epoch 95/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9610 - Precision: 0.8607 - Recall: 0.7820 - accuracy: 0.8231 - loss: 0.4603 - val_AUC: 0.9755 - val_Precision: 0.8889 - val_Recall: 0.8219 - val_accuracy: 0.8836 - val_loss: 0.4031 Epoch 96/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 11ms/step - AUC: 0.9561 - Precision: 0.8110 - Recall: 0.7429 - accuracy: 0.7820 - loss: 0.4803 - val_AUC: 0.9732 - val_Precision: 0.8963 - val_Recall: 0.8288 - val_accuracy: 0.8767 - val_loss: 0.3992 Epoch 97/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9609 - Precision: 0.8306 - Recall: 0.7559 - accuracy: 0.7966 - loss: 0.4662 - val_AUC: 0.9692 - val_Precision: 0.8692 - val_Recall: 0.7740 - val_accuracy: 0.8493 - val_loss: 0.4170 Epoch 98/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9643 - Precision: 0.8520 - Recall: 0.7605 - accuracy: 0.8078 - loss: 0.4363 - val_AUC: 0.9728 - val_Precision: 0.8881 - val_Recall: 0.8151 - val_accuracy: 0.8493 - val_loss: 0.4125 Epoch 99/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9541 - Precision: 0.8060 - Recall: 0.7564 - accuracy: 0.7809 - loss: 0.4989 - val_AUC: 0.9727 - val_Precision: 0.9037 - val_Recall: 0.8356 - val_accuracy: 0.8630 - val_loss: 0.4216 Epoch 100/100 37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9730 - Precision: 0.8528 - Recall: 0.7787 - accuracy: 0.8232 - loss: 0.3842 - val_AUC: 0.9759 - val_Precision: 0.8955 - val_Recall: 0.8219 - val_accuracy: 0.8699 - val_loss: 0.3887
from sklearn.metrics import classification_report, confusion_matrix, ConfusionMatrixDisplay
import matplotlib.pyplot as plt
import numpy as np
# Predicciones del modelo
y_pred_probs_rc = model_rgb_contour.predict(X_test_rc_scaled)
y_pred_labels_rc = np.argmax(y_pred_probs_rc, axis=1)
y_true_labels_rc = np.argmax(Y_test_rc_onehot, axis=1)
# Reporte de clasificación
print("Clasification Report (solo RGB + contorno):")
print(classification_report(y_true_labels_rc, y_pred_labels_rc, digits=4))
# Matriz de confusión
cm_rc = confusion_matrix(y_true_labels_rc, y_pred_labels_rc)
disp_rc = ConfusionMatrixDisplay(confusion_matrix=cm_rc)
disp_rc.plot(cmap='Purples')
plt.title("Matriz de confusión - Modelo RGB + contorno")
plt.grid(False)
plt.show()
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 42ms/step Clasification Report (solo RGB + contorno): precision recall f1-score support 0 0.7500 0.9231 0.8276 39 1 0.7368 0.5385 0.6222 26 2 0.9747 0.9506 0.9625 81 accuracy 0.8699 146 macro avg 0.8205 0.8041 0.8041 146 weighted avg 0.8723 0.8699 0.8659 146
import matplotlib.pyplot as plt
import numpy as np
# Número de ejemplos a mostrar
num_examples = 10
# Selección aleatoria de índices del conjunto de test
indices_rc = np.random.choice(len(X_test_rc), num_examples, replace=False)
# Nombres de las clases (deben coincidir con tu codificación)
class_names = ['Elephant', 'Rhino', 'Others']
# Figura general
plt.figure(figsize=(12, 6 * num_examples // 3))
for i, idx in enumerate(indices_rc):
img = imgs_test_rc[idx]
mask = masks_test_rc[idx] # Máscara correspondiente
true_label = int(y_test_rc[idx]) # Etiqueta real como entero
pred_label = int(y_pred_labels_rc[idx]) # Etiqueta predicha
color = 'green' if true_label == pred_label else 'red' # Color del texto según acierto
# Evitar problemas con valores fuera de rango [0,1]
img_clipped = np.clip(img, 0.0, 1.0)
# Mostrar imagen original
plt.subplot(num_examples, 2, 2 * i + 1)
plt.imshow(img_clipped)
plt.axis('off')
plt.title(f"[IMG] Real: {class_names[true_label]} | Pred: {class_names[pred_label]}", color=color)
# Mostrar máscara binaria
plt.subplot(num_examples, 2, 2 * i + 2)
plt.imshow(mask, cmap='gray')
plt.axis('off')
plt.title("[MASK] Figura binaria", color=color)
plt.suptitle("Predicciones (modelo RGB + contorno)", fontsize=18)
plt.tight_layout()
plt.show()
Comparación de métricas
import matplotlib.pyplot as plt
import numpy as np
# Métricas del modelo completo
metrics_full = {
"Accuracy": accuracy_score(y_test_true_labels, y_test_pred_labels),
"Precision": precision_score(y_test_true_labels, y_test_pred_labels, average='macro', zero_division=0.0),
"Recall": recall_score(y_test_true_labels, y_test_pred_labels, average='macro'),
"F1 Score": f1_score(y_test_true_labels, y_test_pred_labels, average='macro'),
}
# Métricas del modelo RGB + contorno
metrics_rgbc = {
"Accuracy": accuracy_score(y_true_labels_rc, y_pred_labels_rc),
"Precision": precision_score(y_true_labels_rc, y_pred_labels_rc, average='macro', zero_division=0.0),
"Recall": recall_score(y_true_labels_rc, y_pred_labels_rc, average='macro'),
"F1 Score": f1_score(y_true_labels_rc, y_pred_labels_rc, average='macro'),
}
# Preparar gráfico
metric_names = list(metrics_full.keys())
val_full = [metrics_full[m] for m in metric_names]
val_rgbc = [metrics_rgbc[m] for m in metric_names]
x = np.arange(len(metric_names))
width = 0.35
# Plot
plt.figure(figsize=(10, 6))
plt.bar(x - width/2, val_full, width, label='Modelo completo')
plt.bar(x + width/2, val_rgbc, width, label='RGB + contorno')
plt.xticks(x, metric_names)
plt.ylim(0, 1.05)
plt.ylabel('Score')
plt.title('Comparación de métricas entre modelos')
plt.legend()
plt.grid(axis='y', linestyle='--', alpha=0.6)
plt.tight_layout()
plt.show()